949 resultados para Concentration-time response modelling


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Following a malicious or accidental atmospheric release in an outdoor environment it is essential for first responders to ensure safety by identifying areas where human life may be in danger. For this to happen quickly, reliable information is needed on the source strength and location, and the type of chemical agent released. We present here an inverse modelling technique that estimates the source strength and location of such a release, together with the uncertainty in those estimates, using a limited number of measurements of concentration from a network of chemical sensors considering a single, steady, ground-level source. The technique is evaluated using data from a set of dispersion experiments conducted in a meteorological wind tunnel, where simultaneous measurements of concentration time series were obtained in the plume from a ground-level point-source emission of a passive tracer. In particular, we analyze the response to the number of sensors deployed and their arrangement, and to sampling and model errors. We find that the inverse algorithm can generate acceptable estimates of the source characteristics with as few as four sensors, providing these are well-placed and that the sampling error is controlled. Configurations with at least three sensors in a profile across the plume were found to be superior to other arrangements examined. Analysis of the influence of sampling error due to the use of short averaging times showed that the uncertainty in the source estimates grew as the sampling time decreased. This demonstrated that averaging times greater than about 5min (full scale time) lead to acceptable accuracy.

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The tissue distribution kinetics of a highly bound solute, propranolol, was investigated in a heterogeneous organ, the isolated perfused limb, using the impulse-response technique and destructive sampling. The propranolol concentration in muscle, skin, and fat as well as in outflow perfusate was measured up to 30 min after injection. The resulting data were analysed assuming (1) vascular, muscle, skin and fat compartments as well mixed (compartmental model) and (2) using a distributed-in-space model which accounts for the noninstantaneous intravascular mixing and tissue distribution processes but consists only of a vascular and extravascular phase (two-phase model). The compartmental model adequately described propranolol concentration-time data in the three tissue compartments and the outflow concentration-time curve (except of the early mixing phase). In contrast, the two-phase model better described the outflow concentration-time curve but is limited in accounting only for the distribution kinetics in the dominant tissue, the muscle. The two-phase model well described the time course of propranolol concentration in muscle tissue, with parameter estimates similar to those obtained with the compartmental model. The results suggest, first that the uptake kinetics of propranolol into skin and fat cannot be analysed on the basis of outflow data alone and, second that the assumption of well-mixed compartments is a valid approximation from a practical point of view las, e.g., in physiological based pharmacokinetic modelling). The steady-state distribution volumes of skin and fat were only 16 and 4%, respectively, of that of muscle tissue (16.7 ml), with higher partition coefficient in fat (6.36) than in skin (2.64) and muscle (2.79. (C) 2000 Elsevier Science B.V. All rights reserved.

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The outflow-concentration-time profiles for lignocaine (lidocaine) and its metabolites have been measured after bolus impulse administration of [C-14]lignocaine into the perfused rat liver. Livers from female Sprague-Dawley rats were perfused in a once-through fashion with red-blood-cell-free Krebs-Henseleit buffer containing 0 or 2% bovine serum albumin. Perfusate flow rates of 20 and 30 mL min(-1) were used and both normal and retrograde flow directions were employed. Significant amounts of metabolite were detected in the effluent perfusate soon after lignocaine injection. The early appearance of metabolite contributed to bimodal outflow profiles observed for total C-14 radioactivity. The lignocaine outflow profiles were well characterized by the two-compartment dispersion model, with efflux rate << influx rate. The profiles for lignocaine metabolites were also characterized in terms of a simplified two-compartment dispersion model. Lignocaine was found to be extensively metabolized under the experimental conditions with the hepatic availability ranging between 0.09 and 0.18. Generally lignocaine and metabolite availability showed no significant change with alterations in perfusate flow rate from 20 to 30 mt min(-1) or protein content from 0 to 2%. A significant increase in lignocaine availability occurred when 1200 mu M unlabelled lignocaine was added to the perfusate. Solute mean transit times generally decreased with increasing flow rate and with increasing perfusate protein content. The results confirm that lignocaine pharmacokinetics in the liver closely follow the predictions of the well-stirred model. The increase in lignocaine availability when 1200 mu M unlabelled lignocaine was added to the perfusate is consistent with saturation of the hydroxylation metabolic pathways of lignocaine metabolism.

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1. Statistical modelling is often used to relate sparse biological survey data to remotely derived environmental predictors, thereby providing a basis for predictively mapping biodiversity across an entire region of interest. The most popular strategy for such modelling has been to model distributions of individual species one at a time. Spatial modelling of biodiversity at the community level may, however, confer significant benefits for applications involving very large numbers of species, particularly if many of these species are recorded infrequently. 2. Community-level modelling combines data from multiple species and produces information on spatial pattern in the distribution of biodiversity at a collective community level instead of, or in addition to, the level of individual species. Spatial outputs from community-level modelling include predictive mapping of community types (groups of locations with similar species composition), species groups (groups of species with similar distributions), axes or gradients of compositional variation, levels of compositional dissimilarity between pairs of locations, and various macro-ecological properties (e.g. species richness). 3. Three broad modelling strategies can be used to generate these outputs: (i) 'assemble first, predict later', in which biological survey data are first classified, ordinated or aggregated to produce community-level entities or attributes that are then modelled in relation to environmental predictors; (ii) 'predict first, assemble later', in which individual species are modelled one at a time as a function of environmental variables, to produce a stack of species distribution maps that is then subjected to classification, ordination or aggregation; and (iii) 'assemble and predict together', in which all species are modelled simultaneously, within a single integrated modelling process. These strategies each have particular strengths and weaknesses, depending on the intended purpose of modelling and the type, quality and quantity of data involved. 4. Synthesis and applications. The potential benefits of modelling large multispecies data sets using community-level, as opposed to species-level, approaches include faster processing, increased power to detect shared patterns of environmental response across rarely recorded species, and enhanced capacity to synthesize complex data into a form more readily interpretable by scientists and decision-makers. Community-level modelling therefore deserves to be considered more often, and more widely, as a potential alternative or supplement to modelling individual species.

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BACKGROUND: Inter-individual variability in plasma concentration-time profiles might contribute to differences in anti-malarial treatment response. This study investigated the pharmacokinetics of three different forms of artemisinin combination therapy (ACT) in Tanzania and Cambodia to quantify and identify potential sources of variability. METHODS: Drug concentrations were measured in 143 patients in Tanzania (artemether, dihydroartemisinin, lumefantrine and desbutyl-lumefantrine), and in 63 (artesunate, dihydroartemisinin and mefloquine) and 60 (dihydroartemisinin and piperaquine) patients in Cambodia. Inter- and intra-individual variabilities in the pharmacokinetic parameters were assessed and the contribution of demographic and other covariates was quantified using a nonlinear mixed-effects modelling approach (NONMEM®). RESULTS: A one-compartment model with first-order absorption from the gastrointestinal tract fitted the data for all drugs except piperaquine (two-compartment). Inter-individual variability in concentration exposure was about 40% and 12% for mefloquine. From all the covariates tested, only body weight (for all antimalarials) and concomitant treatment (for artemether only) showed a significant influence on these drugs' pharmacokinetic profiles. Artesunate and dihydroartemisinin could not be studied in the Cambodian patients due to insufficient data-points. Modeled lumefantrine kinetics showed that the target day 7 concentrations may not be achieved in a substantial proportion of patients. CONCLUSION: The marked variability in the disposition of different forms of ACT remained largely unexplained by the available covariates. Dosing on body weight appears justified. The concomitance of unregulated drug use (residual levels found on admission) and sub-optimal exposure (variability) could generate low plasma levels that contribute to selecting for drug-resistant parasites.

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This study evaluates the application of an intelligent hybrid system for time-series forecasting of atmospheric pollutant concentration levels. The proposed method consists of an artificial neural network combined with a particle swarm optimization algorithm. The method not only searches relevant time lags for the correct characterization of the time series, but also determines the best neural network architecture. An experimental analysis is performed using four real time series and the results are shown in terms of six performance measures. The experimental results demonstrate that the proposed methodology achieves a fair prediction of the presented pollutant time series by using compact networks.

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the response to an oral calcium load test was assessed in 17 hypercalciuric nephrolithiasis patients who presented elevated parathyroid hormone (PTH) irrespective of the ionized calcium (sCa2+) levels. Blood samples were collected at baseline (0 min) and at 60 and 180 min after 1 g calcium load for serum PTH, total calcium, sCa2+, and 1.25(OH)2D3 determinations. According to the sCa2+ level at baseline, patients were classified as normocalcemic (N = 9) or hypercalcemic (N = 8). Six healthy subjects were also evaluated as controls. Bone mineral density was reduced in 14/17 patients. In the normocalcemic group, mean PTH levels at 0, 60 and 180 min (95 ± 76, 56 ± 40, 57 ± 45 pg/ml, respectively) did not differ from the hypercalcemic group (130 ± 75, 68 ± 35, 80 ± 33 pg/ml) but were significantly higher compared to healthy subjects despite a similar elevation in sCa2+ after 60 and 180 min vs baseline in all 3 groups. Mean total calcium and 1.25(OH)2D3 were similar in the 3 groups. Additionally, we observed that 5 of 9 normocalcemic patients presented a significantly higher concentration-time curve for serum PTH (AUC0',60',180') than the other 4 patients and the healthy subjects, suggesting a primary parathyroid dysfunction. These data suggest that the individual response to an oral calcium load test may be a valuable dynamic tool to disclose a subtle primary hyperparathyroidism in patients with high PTH and fluctuating sCa2+ levels, avoiding repeated measurements of both parameters.

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Objective To describe simultaneous pharmacokinetics (PK) and thermal antinociception after intravenous (IV), intramuscular (IM) and subcutaneous (SC) buprenorphine in cats. Study design Randomized, prospective, blinded, three period crossover experiment. Animals Six healthy adult cats weighing 4.1±0.5kg. Methods Buprenorphine (0.02mgkg-1) was administered IV, IM or SC. Thermal threshold (TT) testing and blood collection were conducted simultaneously at baseline and at predetermined time points up to 24hours after administration. Buprenorphine plasma concentrations were determined by liquid chromatography tandem mass spectrometry. TT was analyzed using anova (p<0.05). A pharmacokinetic-pharmacodynamic (PK-PD) model of the IV data was described using a model combining biophase equilibration and receptor association-dissociation kinetics. Results TT increased above baseline from 15 to 480minutes and at 30 and 60minutes after IV and IM administration, respectively (p<0.05). Maximum increase in TT (mean±SD) was 9.3±4.9°C at 60minutes (IV), 4.6±2.8°C at 45minutes (IM) and 1.9±1.9°C at 60minutes (SC). TT was significantly higher at 15, 60, 120 and 180minutes, and at 15, 30, 45, 60 and 120minutes after IV administration compared to IM and SC, respectively. IV and IM buprenorphine concentration-time data decreased curvilinearly. SC PK could not be modeled due to erratic absorption and disposition. IV buprenorphine disposition was similar to published data. The PK-PD model showed an onset delay mainly attributable to slow biophase equilibration (t1/2ke0=47.4minutes) and receptor binding (kon=0.011mL ng-1minute-1). Persistence of thermal antinociception was due to slow receptor dissociation (t1/2koff=18.2minutes). Conclusions and clinical relevance IV and IM data followed classical disposition and elimination in most cats. Plasma concentrations after IV administration were associated with antinociceptive effect in a PK-PD model including negative hysteresis. At the doses administered, the IV route should be preferred over the IM and SC routes when buprenorphine is administered to cats. © 2012 Association of Veterinary Anaesthetists and the American College of Veterinary Anesthesiologists.

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Electrothermomechanical MEMS are essentially microactuators that operate based on the thermoelastic effect induced by the Joule heating of the structure. They can be easily fabricated and require relatively low excitation voltages. However, the actuation time of an electrothermomechanical microdevice is higher than the actuation times related to electrostatic and piezoelectric actuation principles. Thus, in this research, we propose an optimization framework based on the topology optimization method applied to transient problems, to design electrothermomechanical microactuators for response time reduction. The objective is to maximize the integral of the output displacement of the actuator, which is a function of time. The finite element equations that govern the time response of the actuators are provided. Furthermore, the Solid Isotropic Material with Penalization model and Sequential Linear Programming are employed. Finally, a smoothing filter is implemented to control the solution. Results aiming at two distinct applications suggest the proposed approach can provide more than 50% faster actuators. (C) 2012 Elsevier B.V. All rights reserved.

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Imatinib (IMAT) is a tyrosine kinase inhibitor that has been used for the treatment of chronic myeloid leukemia (CML). Despite the efficacy of IMAT therapy, some cases of treatment resistance have been described in CML. Developing a plasma method is important since there are several studies that provided a higher correlation between IMAT plasma concentration and response to treatment. Therefore, in this investigation we validated a method by CE as an alternative, new, simple and fast electrophoretic method for IMAT determination in human plasma. The analysis was performed using a fused silica capillary (50 mm id x 46.5 cm total length, 38.0 cm effective length); 50 mmol/L sodium phosphate buffer, pH 2.5, as BGE; hydrodynamic injection time of 20 s (50 mbar); voltage of 30 kV; capillary temperature of 35 degrees C and detection at 200 nm. Plasma samples pre-treatment involved liquid-liquid extraction with methyl-tert-butyl ether as the extracting solvent. The method was linear from 0.125 to 5.00 mg/mL. The LOQ was 0.125 mg/mL. Mean absolute recovery of IMAT was 67%. The method showed to be precise and accurate with RSD and relative error values lower than 15%. Furthermore, the application of the method was performed in the analysis of plasma samples from CML patients undergoing treatment with IMAT.

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Time series of vertical sediment fluxes are derived from concentration time series in sheet flow under waves. While the concentrations C(z,t) vary very little with time for \z\ < 10d(50), the measured vertical sediment fluxes Q(zs)(z,t) vary strongly with time in this vertical band and their time variation follows, to some extent, the variation of the grain roughness Shields parameter 02,5(t). Thus, sediment distribution models based on the pickup function boundary condition are in some qualitative agreement with the measurements. However, the pickup function models are only able to model the upward bursts of sediment during the accelerating phases of the flow. They are, so far, unable to model the following strong downward sediment fluxes, which are observed during the periods of flow deceleration. Classical pickup functions, which essentially depend on the Shields parameter, are also incapable of modelling the secondary entrainment fluxes, which sometimes occur at free stream velocity reversal. The measured vertical fluxes indicate that the effective sediment settling velocity in the high [(0.3 < C(z,t) < 0.4] concentration area is typically only a few percent of the clear water settling velocity, while the measurements of Richardson and Jeronimo [Chem. Eng. Sci. 34 (1979) 1419], from a different physical setting, lead to estimates of the order 20%. The data does not support gradient diffusion as a model for sediment entrainment from the bed. That is, detailed modelling of the observed near-bed fluxes would require diffusivities that go negative during periods of flow deceleration. An observed general trend for concentration variability to increase with elevation close to the bed is also irreconcilable with diffusion models driven by a bottom boundary condition. (C) 2002 Published by Elsevier Science B.V.

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This paper presents the measurement, frequency-response modeling and identification, and the corresponding impulse time response of the human respiratory impedance and admittance. The investigated adult patient groups were healthy, diagnosed with chronic obstructive pulmonary disease and kyphoscoliosis, respectively. The investigated children patient groups were healthy, diagnosed with asthma and cystic fibrosis, respectively. Fractional order (FO) models are identified on the measured impedance to quantify the respiratory mechanical properties. Two methods are presented for obtaining and simulating the time-domain impulse response from FO models of the respiratory admittance: (i) the classical pole-zero interpolation proposed by Oustaloup in the early 90s, and (ii) the inverse discrete Fourier Transform (DFT). The results of the identified FO models for the respiratory admittance are presented by means of their average values for each group of patients. Consequently, the impulse time response calculated from the frequency response of the averaged FO models is given by means of the two methods mentioned above. Our results indicate that both methods provide similar impulse response data. However, we suggest that the inverse DFT is a more suitable alternative to the high order transfer functions obtained using the classical Oustaloup filter. Additionally, a power law model is fitted on the impulse response data, emphasizing the intrinsic fractal dynamics of the respiratory system.

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Hyperspectral instruments have been incorporated in satellite missions, providing large amounts of data of high spectral resolution of the Earth surface. This data can be used in remote sensing applications that often require a real-time or near-real-time response. To avoid delays between hyperspectral image acquisition and its interpretation, the last usually done on a ground station, onboard systems have emerged to process data, reducing the volume of information to transfer from the satellite to the ground station. For this purpose, compact reconfigurable hardware modules, such as field-programmable gate arrays (FPGAs), are widely used. This paper proposes an FPGA-based architecture for hyperspectral unmixing. This method based on the vertex component analysis (VCA) and it works without a dimensionality reduction preprocessing step. The architecture has been designed for a low-cost Xilinx Zynq board with a Zynq-7020 system-on-chip FPGA-based on the Artix-7 FPGA programmable logic and tested using real hyperspectral data. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low-cost embedded systems, opening perspectives for onboard hyperspectral image processing.

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1st ASPIC International Congress

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The pharmacokinetic profile of imatinib has been assessed in healthy subjects and in population studies among thousands of patients with CML or GIST. Imatinib is rapidly and extensively absorbed from the GI tract, reaching a peak plasma concentration (Cmax) within 1-4 h following administration. Imatinib bioavailability is high (98%) and independent of food intake. Imatinib undergoes rapid and extensive distribution into tissues, with minimal penetration into the central nervous system. In the circulation, it is approximately 95% bound to plasma proteins, principally α1-acid glycoprotein (AGP) and albumin. Imatinib undergoes metabolism in the liver via the cytochrome P450 enzyme system (CYP), with CYP3A4 being the main isoenzyme involved. The N-desmethyl metabolite CGP74588 is the major circulating active metabolite. The typical elimination half-life for imatinib is approximately 14-22 h. Imatinib is characterized by large inter-individual pharmacokinetic variability, which reflects in a wide spread of concentrations observed under standard dosage. Besides adherence, several factors have been shown to influence this variability, especially demographic characteristics (sex, age, body weight and disease diagnosis), blood count characteristics, enzyme activity (mainly CYP3A4), drug interactions, activity of efflux transporters and plasma levels of AGP. Additionally, recent retrospective studies have shown that drug exposure, reflected in either the area under the concentration-time curve (AUC) or more conveniently the trough level (Cmin), correlates with treatment outcomes. Increased toxicity has been associated with high plasma levels, and impaired clinical efficacy with low plasma levels. While no upper concentration limit has been formally established, a lower limit for imatinib Cmin of about 1000 ng/mL has been proposed repeatedly for improving outcomes in CML and GIST patients. Imatinib is licensed for use in chronic phase CML and GIST at a fixed dose of 400 mg once daily (600 mg in some other indications) despite substantial pharmacokinetic variability caused by both genetic and acquired factors. The dose can be modified on an individual basis in cases of insufficient response or substantial toxic effects. Imatinib would, however, meet traditional criteria for a therapeutic drug monitoring (TDM) program: long-term therapy, measurability, high inter-individual but restricted intra-individual variability, limited pharmacokinetic predictability, effect of drug interactions, consistent association between concentration and response, suggested therapeutic threshold, reversibility of effect and absence of early markers of efficacy and toxic effects. Large-scale, evidence-based assessments of drug concentration monitoring are therefore still warranted for the personalization of imatinib treatment.