986 resultados para Continuous Maps


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In this paper, Bayesian decision procedures are developed for dose-escalation studies based on binary measures of undesirable events and continuous measures of therapeutic benefit. The methods generalize earlier approaches where undesirable events and therapeutic benefit are both binary. A logistic regression model is used to model the binary responses, while a linear regression model is used to model the continuous responses. Prior distributions for the unknown model parameters are suggested. A gain function is discussed and an optional safety constraint is included. Copyright (C) 2006 John Wiley & Sons, Ltd.

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Details about the parameters of kinetic systems are crucial for progress in both medical and industrial research, including drug development, clinical diagnosis and biotechnology applications. Such details must be collected by a series of kinetic experiments and investigations. The correct design of the experiment is essential to collecting data suitable for analysis, modelling and deriving the correct information. We have developed a systematic and iterative Bayesian method and sets of rules for the design of enzyme kinetic experiments. Our method selects the optimum design to collect data suitable for accurate modelling and analysis and minimises the error in the parameters estimated. The rules select features of the design such as the substrate range and the number of measurements. We show here that this method can be directly applied to the study of other important kinetic systems, including drug transport, receptor binding, microbial culture and cell transport kinetics. It is possible to reduce the errors in the estimated parameters and, most importantly, increase the efficiency and cost-effectiveness by reducing the necessary amount of experiments and data points measured. (C) 2003 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

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Gluco-oligosaccharides produced by Gluconobacter oxydans NCIMB 4943 from maltodextrin as the source, were evaluated for their fermentability by the human colonic microflora. The selectivity of growth of desirable bacteria in the human colon was studied in a three-stage continuous model of the human large intestine. Populations of bacteria, and their fluctuations as a response to the fermentation, were enumerated using fluorescent in situ hybridization (FISH). The gluco-oligosaccharides resulted in increases in numbers of bifidobacteria and the Lactobacillus/Enterococcus group in all 3 vessels of the system, representing the proximal, transverse and distal colonic areas. The prebiotic indices of the glucooligosaccharides were 2.29, 4.23 and 2.74 in V1, V2 and V3 respectively.

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Truly continuous solid-state fermentations with operating times of 2-3 weeks were conducted in a prototype bioreactor for the production of fungal (Penicillium glabrum) tannase from a tannin-containing model substrate. Substantial quantities of the enzyme were synthesized throughout the operating periods and (imperfect) steady-state conditions seemed to be achieved soon after start-up of the fermentations. This demonstrated for the first time the possibility of conducting solid-state fermentations in the continuous mode and with a constant noninoculated feed. The operating variables and fermentation conditions in the bioreactor were sufficiently well predicted for the basic reinoculation concept to succeed. However, an incomplete understanding of the microbial mechanisms, the experimental system, and their interaction indicated the need for more research in this novel area of solid-state fermentation. (C) 2004 Wiley Periodicals, Inc.

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Prebiotics are nondigestible food ingredients that encourage proliferation of selected groups of the colonic microflora, thereby altering the composition toward a more beneficial community. In the present study, the prebiotic potential of a novel galactooligosaccharide (GOS) mixture, produced by the activity of galactosyltransferases from Bifidobacterium bifidum 41171 on lactose, was assessed in vitro and in a parallel continuous randomized pig trial. In situ fluorescent hybridization with 16S rRNA-targeted probes was used to investigate changes in total bacteria, bifidobacteria, lactobacilli, bacteroides, and Clostridium histolyticum group in response to supplementing the novel GOS mixture. In a 3-stage continuous culture system, the bifidobacterial numbers for the first 2 vessels, which represented the proximal and traverse colon, increased (P < 0.05) after the addition of the oligosaccharide mixture. In addition, the oligosaccharide mixture strongly inhibited the attachment of enterohepatic Escherichia coli (P < 0.01) and Salmonella enterica serotype Typhimurium (P < 0.01) to HT29 cells. Addition of the novel mixture at 4% (wt:wt) to a commercial diet increased the density of bificlobacteria (P < 0.001) and the acetate concentration (P < 0.001), and decreased the pH (P < 0.001) compared with the control diet and the control diet supplemented with inulin, suggesting a great prebiotic potential for the novel oligosaccharide mixture. J. Nutr. 135: 1726-1731, 2005.

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In vitro fermentations were carried out by using a model of the human colon to simulate microbial activities of lower gut bacteria. Bacterial populations (and their metabolic products) were evaluated under the effects of various fermentable substrates. Carbohydrates tested were polydextrose, lactitol, and fructo-oligosaccharide (FOS). Bacterial groups of interest were evaluated by fluorescence in situ hybridization as well as by species-specific PCR to determine bifidobacterial species and percent-G+C profiling of the bacterial communities present. Short-chain fatty acids (SCFA) produced during the fermentations were also evaluated. Polydextrose had a stimulatory effect upon colonic bifidobacteria at concentrations of 1 and 2% (using a single and pooled human fecal inoculum, respectively). The bifidogenic effect was sustained throughout all three vessels of the in vitro system (P = 0.01 seen in vessel 3), as corroborated by the bacterial community profile revealed by %G+C analysis. This substrate supported a wide variety of bifidobacteria and was the only substrate where Bifidobacterium infantis was detected. The fermentation of lactitol had a deleterious effect on both bifidobacterial and bacteroides populations (P = 0.01) and decreased total cell numbers. SCFA production was stimulated, however, particularly butyrate (beneficial for host colonocytes). FOS also had a stimulatory effect upon bifidobacterial and lactobacilli populations that used a single inoculum (P = 0.01 for all vessels) as well as a bifidogenic effect in vessels 2 and 3 (P = 0.01) when a pooled inoculum was used. A decrease in bifidobacteria throughout the model was reflected in the percent-G+C profiles.

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A study of galacto-oligosaccharides (GOS) synthesis from lactose with beta-galactosidase from Kluyveromyces lactis (Maxilact(R) L2000) was carried out. The synthesis was performed using various initial lactose concentrations ranging from 220 to 400 mg/mL and enzyme concentrations ranging from 3 to 9 U/mL, and was investigated at 40degreesC and pH 7, in a stirred-tank reactor. In the experimental range examined, the results showed the amount of GOS formed depended on lactose concentration but not on enzyme concentration. Galactose was a competitive inhibitor, while glucose was a non-competitive inhibitor. In a further study, a laboratory-scale reactor system, fitted with a 10-kDa NMWCO composite regenerated cellulose membrane, was used in a continuous process. The reactor was operated in cross-flow mode. The effect of operating pressures on flux and productivity was investigated by applying different transmembrane pressures to the system. The continuous process showed better production performance compared to the batch synthesis with the same lactose and enzyme concentrations at 40degreesC, pH 7. Comparison of product structures from batch and continuous processes, analyzed by HPAEPAD and methylation analysis, showed similarities but differed from the structures found in a commercial GOS product (Vivinal(R)GOS). (C) 2004 Wiley Periodicals, Inc.

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Aims: Certain milk factors may promote the growth of a gastrointestinal microflora predominated by bifidobacteria and may aid in overcoming enteric infections. This may explain why breast-fed infants experience fewer intestinal infections than their formula-fed counterparts. The effect of formula supplementation with two such factors was investigated in this study. Methods and Results: Infant faecal specimens were used to ferment formulae supplemented with glycomacropeptide (GMP) and alpha-lactalbumin (alpha-la) in a two-stage compound continuous culture model. At steady state, all fermenter vessels were inoculated with 5 ml of 0.1 M phosphate-buffered saline (pH 7.2) containing 10(8) CFU ml(-1) of either enteropathogenic Escherichia coli 2348/69 (O127:H6) or Salmonella serotype Typhimurium (DSMZ 5569). Bacteriology was determined by independent fluorescence in situ hybridization. Vessels that contained breast milk (BM), as well as alpha-la and GMP supplemented formula had stable total counts of bifidobacteria while lactobacilli increased significantly only in vessels with breast milk. Bacteroides, clostridia and E. coli decreased significantly in all three groups prior to pathogen addition. Escherichia coli counts decreased in vessels containing BM and alpha-la while Salmonella decreased significantly in all vessels containing BM, alpha-la and GMP. Acetate was the predominant acid. Significance and Impact of the Study: Supplementation of infant formulae with appropriate milk proteins may be useful in mimicking the beneficial bacteriological effects of breast milk.

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In this paper, we present an on-line estimation algorithm for an uncertain time delay in a continuous system based on the observational input-output data, subject to observational noise. The first order Pade approximation is used to approximate the time delay. At each time step, the algorithm combines the well known Kalman filter algorithm and the recursive instrumental variable least squares (RIVLS) algorithm in cascade form. The instrumental variable least squares algorithm is used in order to achieve the consistency of the delay parameter estimate, since an error-in-the-variable model is involved. An illustrative example is utilized to demonstrate the efficacy of the proposed approach.

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The usefulness of motor subtypes of delirium is unclear due to inconsistency in subtyping methods and a lack of validation with objective measures of activity. The activity of 40 patients was measured over 24 h with a discrete accelerometer-based activity monitor. The continuous wavelet transform (CWT) with various mother wavelets were applied to accelerometry data from three randomly selected patients with DSM-IV delirium that were readily divided into hyperactive, hypoactive, and mixed motor subtypes. A classification tree used the periods of overall movement as measured by the discrete accelerometer-based monitor as determining factors for which to classify these delirious patients. This data used to create the classification tree were based upon the minimum, maximum, standard deviation, and number of coefficient values, generated over a range of scales by the CWT. The classification tree was subsequently used to define the remaining motoric subtypes. The use of a classification system shows how delirium subtypes can be categorized in relation to overall motoric behavior. The classification system was also implemented to successfully define other patient motoric subtypes. Motor subtypes of delirium defined by observed ward behavior differ in electronically measured activity levels.

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The ability of four operational weather forecast models [ECMWF, Action de Recherche Petite Echelle Grande Echelle model (ARPEGE), Regional Atmospheric Climate Model (RACMO), and Met Office] to generate a cloud at the right location and time (the cloud frequency of occurrence) is assessed in the present paper using a two-year time series of observations collected by profiling ground-based active remote sensors (cloud radar and lidar) located at three different sites in western Europe (Cabauw. Netherlands; Chilbolton, United Kingdom; and Palaiseau, France). Particular attention is given to potential biases that may arise from instrumentation differences (especially sensitivity) from one site to another and intermittent sampling. In a second step the statistical properties of the cloud variables involved in most advanced cloud schemes of numerical weather forecast models (ice water content and cloud fraction) are characterized and compared with their counterparts in the models. The two years of observations are first considered as a whole in order to evaluate the accuracy of the statistical representation of the cloud variables in each model. It is shown that all models tend to produce too many high-level clouds, with too-high cloud fraction and ice water content. The midlevel and low-level cloud occurrence is also generally overestimated, with too-low cloud fraction but a correct ice water content. The dataset is then divided into seasons to evaluate the potential of the models to generate different cloud situations in response to different large-scale forcings. Strong variations in cloud occurrence are found in the observations from one season to the same season the following year as well as in the seasonal cycle. Overall, the model biases observed using the whole dataset are still found at seasonal scale, but the models generally manage to well reproduce the observed seasonal variations in cloud occurrence. Overall, models do not generate the same cloud fraction distributions and these distributions do not agree with the observations. Another general conclusion is that the use of continuous ground-based radar and lidar observations is definitely a powerful tool for evaluating model cloud schemes and for a responsive assessment of the benefit achieved by changing or tuning a model cloud