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PubMed2005

The correlation between genomic G+C and optimal growth temperature of prokaryotes is robust: a reply to Marashi and Ghalanbor.

We have recently shown that optimal growth temperature (T(opt)) is one of the factors that influence genomic GC in prokaryotes. Our results have been disputed by Marashi and Ghalanbor, who claim that the correlations we show are not "robust" because the elimination of some points (arbitrarily chosen) leads, in some families, to variations in the correlation coefficients and/or significance of correlations. Here, we test whether the correlation between T(opt) and genomic GC is robust by using two independent approaches: detection of possible outliers (using robust Mahalanobis distance) and usage of a non-parametric correlation coefficient that is not sensitive to the presence of outliers. The results presented here reinforce our previous proposal that T(opt) is correlated with genomic GC in prokaryotes.

Cytosine↗
PubMed2004

Robustness of cellular functions.

Robustness, the ability to maintain performance in the face of perturbations and uncertainty, is a long-recognized key property of living systems. Owing to intimate links to cellular complexity, however, its molecular and cellular basis has only recently begun to be understood. Theoretical approaches to complex engineered systems can provide guidelines for investigating cellular robustness because biology and engineering employ a common set of basic mechanisms in different combinations. Robustness may be a key to understanding cellular complexity, elucidating design principles, and fostering closer interactions between experimentation and theory.

Animals↗
PubMed2004

Reversed-phase liquid chromatography column testing: robustness study of the test.

Choosing the right RPLC column for an actual separation among the more than 600 commercially available ones still represents a real challenge for the analyst particularly when basic solutes are involved. Many tests dedicated to the characterization and the classification of stationary phases have been proposed in the literature and some of them highlighted the need of a better understanding of retention properties to lead to a rational choice of columns. However, unlike classical chromatographic methods, the problem of their robustness evaluation has often been left unaddressed. In the present study, we present a robustness study that was applied to the chromatographic testing procedure we had developed and optimized previously. A design of experiment (DoE) approach was implemented. Four factors, previously identified as potentially influent, were selected and subjected to small controlled variations: solvent fraction, temperature, pH and buffer concentration. As our model comprised quadratic terms instead of a simple linear model, we chose a D-optimal design in order to minimize the experiment number. As a previous batch-to-batch study [K. Le Mapihan, Caractérisation et classification des phases stationnaires utilisées pour l'analyse CPL de produits pharmaceutiques, Ph.D. Thesis, Pierre and Marie Curie University, 2004] had shown a low variability on the selected stationary phase, it was then possible to split the design into two parts, according to the solvent nature, each using one column. Actually, our testing procedure involving assays both with methanol and with acetonitrile as organic modifier, such an approach enabled to avoid a possible bias due to the column ageing considering the number of experiments required (16 + 6 center points). Experimental results were computed thanks to a Partial Least Squares regression procedure, more adapted than the classical regression to handle factors and responses not completely independent. The results showed the behavior of the solutes in relation to their physico-chemical properties and the relevance of the second term degree of our model. Finally, the robust domain of the test has been fairly identified, so that any potential user precisely knows to which extend each experimental parameter must be controlled when our testing procedure is to be implemented.

Chromatography, Liquid↗
PubMed2005

Using computer simulation to assist in the robustness analysis of an ion-exchange chromatography step.

This paper presents a methodology to gain process knowledge and assist in the robustness analysis of an ion-exchange step in a protein purification process using a model-based approach. Factorial experimental design is common practice in industry today to obtain robustness characterization of unit operations with respect to variations in process parameters. This work aims at providing a better insight into what process variations affect quality and to further reduce the experimental work to the regions of process variation that are of most interest. This methodology also greatly increases the ability to predict process performance and promotes process understanding. The model calibration part of the methodology involves three consecutive steps to calibrate a steric mass action (SMA) ion-exchange chromatography model. Firstly, a number of gradient elution experiments are performed. Secondly, experimental breakthrough curves have to be generated for the proteins if the adsorption capacity of the medium for each component is not known. Thirdly, a multi-component loading experiment is performed to calibrate the multi-component effects that cannot be determined from the single-component experiments. The separation process studied in this work is the separation of polyclonal IgG from a mixture containing IgG, myoglobin and BSA. The calibrated model is used to simulate six process variations in a full factorial experiment. The results of the simulations provide information about the importance of the different process variations and the simulations are also used to determine the crucial points for the process parameter variations. The methodology can be used to assist in the robustness analysis normally performed in the pharmaceutical industry today as it is able to predict the impact on process performance resulting from variations in salt concentration, column load, protein concentration and flow rate.

Chromatography, Gel↗
PubMed2005

Enantiomeric determination, validation and robustness studies of racemic citalopram in pharmaceutical formulations by capillary electrophoresis.

A chiral capillary electrophoresis (CE) method has been developed allowing the enantiomeric separation of racemic citalopram (R-(-) and S-(+) citalopram) using as chiral selector carboxymethyl-gamma-cyclodrextrin (CM-gamma-CD). The influence of chemical and instrumental parameters on the separation such as cyclodextrin (CD) and buffer concentrations, buffer pH, voltage, injection pressure, ..., was investigated. Good chiral separation of the racemic mixture was achieved in less than 4 min using a fused-silica capillary and as background electrolyte (BGE) a phosphate buffer solution (20 mM, pH 7) containing 0.15% (w/v) of CM-gamma-CD as chiral selector. The separation was driven in normal polarity mode at 15 degrees C, 30 kV and hydrodynamic injection. In order to validate the method, the stability of the solutions, precision (repeatability, reproducibility and F-Snedecor test), linearity (Lack of Fit and ANOVA tests) accuracy (98-101%), detection and quantitation limits (0.06 and 0.2 mg L(-1), respectively), on a selected analytical placebo, were examined. Besides, a robustness test was performed using the Plackett-Burman fractional factorial experimental design using a matrix of 15 experiments for seven factors (internal parameters) with a statistical treatment suggested by Youden and Steinner. The proposed method is fast, sensitive, inexpensive and, besides, it has been evaluated by means of an extensive validation study and an exhaustive robustness test. The scope of this validated and robust method has been proved in the analysis of four pharmaceutical formulations; two of them (recently available in Spain), which just contained S-(+)-citalopram (escitalopram) as active principle. Recoveries between 101 and 103%, with regard to their nominal contents were obtained. In the other two pharmaceutical ones, the method provided the separation and quantification of both chiral isomers in the existing racemic mixture.

Citalopram↗
PubMed2005

Robust tests for the multivariate Behrens-Fisher problem.

Hotelling's T2 procedure is used to test the equality of means in two-group multivariate designs when covariances are homogeneous. A number of alternatives to T2, which are robust to covariance heterogeneity, have been proposed in the literature. However, all are sensitive to departures from multivariate normality. We demonstrate how to obtain multivariate tests that are robust to covariance heterogeneity and non-normality with estimators of location and scale based on trimming and Winsorizing. The performance of six alternatives to T2 was examined via Monte Carlo methods when characteristics of the research design, degree of covariance heterogeneity, and degree of non-normality were manipulated. We have recently developed a program written in the SAS/IML language that can be used to implement these robust multivariate tests. Recommendations are provided on the specific data-analytic conditions under which these tests should be adopted.

Analysis of Variance↗
PubMed2006

Robust rigid registration of retinal angiograms through optimization.

Retinal fundus photographs are employed as standard diagnostic tools in ophthalmology. Serial photographs of the flow of fluorescein and indocyanine green (ICG) dye are used to determine the areas of the retinal lesions. For objective measurements of features, the registration of the images is a necessity. In this paper, we employ optimization techniques for registration with the help of 2-parameter translational motion model of retinal angiograms, based on non-linear pre-processing (Wiener filtering and morphological gradient) and computation of the similarity criteria for the alignment of the two gradient images for any given rigid transformation. The optimization methods are effectively employed to minimize the similarity criterion. The presence of noise, the variations in the background and the temporal variation of the fluorescence level pose serious problems in obtaining a robust registration of the retinal images. Moreover, local search strategies are not robust in the case of ICG angiograms, even if one uses a multiresolution approach. The present work makes a systematic comparison of different optimization techniques, namely the minimization method derived from the optical flow formulation, the Nelder-Mead local search and the HCIAC ant colony metaheuristic, each optimizing a similarity criterion for the gradient images. The impact of the resolution and median filtering of gradient image is studied and the robustness of the approaches is tested through experimental studies, performed on macular fluorescein and ICG angiographies. Our proposed optimization techniques have shown interesting results especially for high resolution difficult registration problems. Moreover, this approach seems promising for affine (6-parameter motion model) or elastical registrations.

Algorithms↗
PubMed2004

Evaluation of the robustness of FT-IR spectra of lactobacilli towards changes in the bacterial growth conditions.

In order to use Fourier Transform Infrared (FT-IR) spectroscopy for identification of microorganisms on a routine basis, it is important that the spectra are robust against small, uncontrollable variations in the bacterial growth conditions. In this study, the effect of small variations in growth temperature, growth time, growth medium and atmospheric conditions on the separation of Lactobacillus based on their FT-IR spectra was investigated. The resulting spectra were shown to be robust against the variations in the cultivation conditions, and the separation of both strains and species was unaffected. Larger variations in the growth medium influenced only the separation of strains. FT-IR spectroscopy for identification of lactobacilli therefore seems to be robust against small variations in the cultivation conditions.

Aerobiosis↗
PubMed2004

The robustness of dose distributions to displacement and migration of 125I permanent seed implants over a wide range of seed number, activity, and designs.

PURPOSE: To investigate the robustness of permanent prostate implant dosimetry for various (125)I seed activities and various seed models. The dosimetric impact of seed misplacement and seed migration (seed loss) is also taken into account using various standard dose indices. METHODS AND MATERIALS: A dose-based inverse planning algorithm is used for automated dosimetric plan creation (45-60 s per plan) and provides an unbiased way to compare the robustness of various optimal dosimetric plans. Seed misplacement and seed migration are simulated by way of Monte Carlo, based on the measured displacement distributions from clinical postimplant cases. Plans were generated for seed activities between 0.2 and 1.4 mCi (0.25 to 1.78 U) and for 11 different seed models. RESULTS: The numbers of seeds and needles are shown to decrease rapidly for a seed activity between 0.3 mCi and 0.6 mCi (0.38 and 0.76 U). The loss in V100, from 100%, because of seed misplacement is below 10% for an apparent activity ranging from 0.2 to 0.9 mCi (0.25 to 1.14 U). A minimum degradation in V100 is observed around 0.6-0.7 mCi (0.76-0.89 U). D90 increases from 150 to 170 Gy between 0.3 and 0.7 mCi (0.38 and 0.89 U) and decreases afterward to fall below 140 Gy at higher activity. V200 and D10 to the target volume both show an increase in hot spots up to 0.7 mCi, and then decrease linearly at higher activities for all seed models. V200 and D10 to the urethra remain about constant for all seed activities up to 0.8 mCi (1.02 U), at which point they start to decrease. All seed models follow this general trend. CONCLUSIONS: Plans were shown to be robust to misplacement and migration of seeds over a wide range of seed activity and for various seed models. With a properly tuned inverse planning algorithm able to ensure the dose coverage and protection for the organs at risk in the presence of placement errors (displacement and migration), the choice of a preferred seed activity, in a range up to about 0.7 mCi (0.89 U), is open. The upper part of this range offers the opportunity to significantly reduce the number of seeds and needles, thus reducing surgical trauma to the patient, saving time in an operating room planning setting, and reducing the cost of a permanent prostate implant procedure.

Algorithms↗
PubMed2005

Dynamic optimization of bioprocesses: efficient and robust numerical strategies.

The dynamic optimization (open loop optimal control) of non-linear bioprocesses is considered in this contribution. These processes can be described by sets of non-linear differential and algebraic equations (DAEs), usually subject to constraints in the state and control variables. A review of the available solution techniques for this class of problems is presented, highlighting the numerical difficulties arising from the non-linear, constrained and often discontinuous nature of these systems. In order to surmount these difficulties, we present several alternative stochastic and hybrid techniques based on the control vector parameterization (CVP) approach. The CVP approach is a direct method which transforms the original problem into a non-linear programming (NLP) problem, which must be solved by a suitable (efficient and robust) solver. In particular, a hybrid technique uses a first global optimization phase followed by a fast second phase based on a local deterministic method, so it can handle the nonconvexity of many of these NLPs. The efficiency and robustness of these techniques is illustrated by solving several challenging case studies regarding the optimal control of fed-batch bioreactors and other bioprocesses. In order to fairly evaluate their advantages, a careful and critical comparison with several other direct approaches is provided. The results indicate that the two-phase hybrid approach presents the best compromise between robustness and efficiency.

Algorithms↗
PubMed2006

IFRP: a hybrid interval-parameter fuzzy robust programming approach for waste management planning under uncertainty.

In this study, an interval-parameter fuzzy-robust programming (IFRP) model is developed and applied to the planning of solid waste management systems under uncertainty. As an extension of the existing fuzzy-robust programming and interval-parameter linear programming methods, the IFRP can explicitly address system uncertainties with complex presentations. Parameters in the IFRP model can be represented as interval numbers and/or fuzzy membership functions, such that the uncertainties can be directly communicated into the optimization process and resulting solution. Furthermore, highly uncertain information for the lower and upper bounds of interval parameters that exist due to the complexity of the real world can be effectively handled through introducing the concept of fuzzy boundary interval. Consequently, robustness of the optimization process and solution can be enhanced. Results of the case study indicate that useful solutions for planning municipal solid waste management practices can be generated. They reflect a compromise between optimality and stability of the study system. Willingness to pay higher costs will guarantee the system stability; however, a desire to reduce the costs will run the risk of potential instability of the system. The results also suggest that the proposed hybrid methodology is applicable to practical problems that are associated with highly complex and uncertain information.

Algorithms↗
PubMed2006

Food webs robustness to biodiversity loss: the roles of connectance, expansibility and degree distribution.

We analyse the robustness of food webs against species loss by considering the influence of several structural factors of the networks, such as connectance, degree distribution and expansibility. The last concept refers to the absence of structural bottlenecks in the food web, whose removal separate the network into large isolate clusters. In theory networks with identical connectance can display different expansibility characteristics. Using the spectral scaling method we studied 17 food networks and classified them as good expansion (GE) and not-GE networks. The combination of GE properties and degree distribution of species permitted the classification of food webs into six different classes. These classes characterize the differences in robustness of food webs to species loss. While the webs having uniform degree distributions and displaying GE properties are the most robust to species loss, the presence of bottlenecks and skewed distribution of the number of links per species make food webs very vulnerable to primary removal of species.

Animals↗
PubMed2005

Confhusius: a robust and fully automatic calibration method for 3D freehand ultrasound.

This paper describes a new robust and fully automatic method for calibration of three-dimensional (3D) freehand ultrasound called Confhusius (CalibratiON for FreeHand UltraSound Imaging USage). 3D Freehand ultrasound consists in mounting a position sensor on a standard probe. The echographic B-scans can be localized in 3D and compounded into a volume. However, especially for quantitative use, this process dramatically requires a calibration procedure that determines its accuracy and usefulness. Calibration aims at determining the transformation (translations, rotations, scaling) between the coordinates system of the echographic images and the coordinate system of the localization system. To calibrate, we acquire images of a phantom whose 3D geometrical properties are known. We propose a robust and fully automatic calibration method based on the Hough transform and robust estimators. Experiments have been done with synthetic and real sequences, and this calibration method is shown to be easy to perform, accurate, automatic and fast enough for clinical use.

Calibration↗
PubMed2005

Fetal hippocampal CA3 cell grafts enriched with FGF-2 and BDNF exhibit robust long-term survival and integration and suppress aberrant mossy fiber sprouting in the injured middle-aged hippocampus.

Cell transplants that successfully replace the lost neurons and facilitate the reconstruction of the disrupted circuitry in the injured aging hippocampus are invaluable for treating acute head injury, stroke and status epilepticus in the elderly. This is because apt graft integration has the potential to prevent the progression of the acute injury into chronic epilepsy in the elderly. However, neural transplants into the injured middle-aged or aged hippocampus exhibit poor cell survival, suggesting that apt graft augmentation strategies are critical for robust integration of grafted cells into the injured aging hippocampus. We examined the efficacy of pre-treatment and grafting of donor fetal CA3 cells with a blend of fibroblast growth factor-2 (FGF-2) and brain-derived neurotrophic factor (BDNF) for lasting survival and integration of grafted cells in the injured middle-aged (12 months old) hippocampus of F344 rats. Grafts were placed at 4 days after the kainic-acid-induced hippocampal injury and were analyzed at 6 months post-grafting. We demonstrate that 80% of grafted cells exhibit prolonged survival and 71% of grafted cells differentiate into CA3 pyramidal neurons. Grafts also receive a robust afferent input from the host mossy fibers and project efferent axons into the denervated zones of the dentate gyrus and the CA1 subfield. Consequently, the aberrant sprouting of the dentate mossy fibers, an epileptogenic change that typically ensues after the hippocampal injury, was suppressed. Thus, grafts of fetal CA3 cells enriched with FGF-2 and BDNF exhibit robust integration and dampen the abnormal mossy fiber sprouting in the injured middle-aged hippocampus. Because the aberrantly sprouted mossy fibers contribute to the generation of seizures, the results suggest that the grafting intervention using FGF-2 and BDNF is efficacious for suppressing epileptogenesis in the injured middle-aged hippocampus.

Animals↗
PubMed2005

TAO-robust backpropagation learning algorithm.

In several fields, as industrial modelling, multilayer feedforward neural networks are often used as universal function approximations. These supervised neural networks are commonly trained by a traditional backpropagation learning format, which minimises the mean squared error (mse) of the training data. However, in the presence of corrupted data (outliers) this training scheme may produce wrong models. We combine the benefits of the non-linear regression model tau-estimates [introduced by Tabatabai, M. A. Argyros, I. K. Robust Estimation and testing for general nonlinear regression models. Applied Mathematics and Computation. 58 (1993) 85-101] with the backpropagation algorithm to produce the TAO-robust learning algorithm, in order to deal with the problems of modelling with outliers. The cost function of this approach has a bounded influence function given by the weighted average of two psi functions, one corresponding to a very robust estimate and the other to a highly efficient estimate. The advantages of the proposed algorithm are studied with an example.

Algorithms↗
PubMed2003

A rapid algorithm for robust and automatic extraction of the midsagittal plane of the human cerebrum from neuroimages based on local symmetry and outlier removal.

A rapid algorithm for robust, accurate, and automatic extraction of the midsagittal plane (MSP) of the human cerebrum from normal and pathological neuroimages is proposed. The MSP is defined as a plane formed from the interhemispheric fissure line segments having the dominant orientation. The algorithm extracts the MSP in four steps: (1) determine suitable axial slices for processing, (2) localize the fissure line segments on them, (3) select inliers from the extracted fissure line segments through histogram-based outlier removal, and (4) calculate the equation of the MSP from the selected inliers. The fissure line segments are localized by minimizing the local symmetry index characterizing anatomical properties of images in the vicinity of the interhemispheric fissure. A two-stage angular and distance outlier removal is introduced to handle abnormalities. The algorithm has been validated quantitatively with 125 structural MRI and CT cases from 10 centers on three continents by studying its accuracy; tolerance to rotation, noise, asymmetry, and bias field; sensitivity to parameters; and performance. A statistical relationship between algorithm accuracy and the data's adherence to planarity is also determined. The algorithm extracts the MSP below 6 s on Pentium 4 (2.4 GHz) with the average angular and distance errors of (0.40 degrees; 0.63 mm) for normal and (0.59 degrees; 0.73 mm) for pathological cases. The robustness to noise, asymmetry, rotation, and bias field is achieved by extracting the MSP based on the dominant orientation and local symmetry index. A low computational cost results from applying simple operations capturing intrinsic anatomic features, constraining the searching space to the local vicinity of the interhemispheric fissure, and formulating a noniterative algorithm with a coarse and fine fixed-step searching. In comparison to the existing methods, our algorithm is much faster, performs accurately and robustly for a wide range of diversified data, and is fully automatic and thoroughly validated, which make it suitable for clinical applications.

Acoustic Stimulation↗
PubMed2004

Fast and robust parameter estimation for statistical partial volume models in brain MRI.

Due to the finite spatial resolution of imaging devices, a single voxel in a medical image may be composed of mixture of tissue types, an effect known as partial volume effect (PVE). Partial volume estimation, that is, the estimation of the amount of each tissue type within each voxel, has received considerable interest in recent years. Much of this work has been focused on the mixel model, a statistical model of PVE. We propose a novel trimmed minimum covariance determinant (TMCD) method for the estimation of the parameters of the mixel PVE model. In this method, each voxel is first labeled according to the most dominant tissue type. Voxels that are prone to PVE are removed from this labeled set, following which robust location estimators with high breakdown points are used to estimate the mean and the covariance of each tissue class. Comparisons between different methods for parameter estimation based on classified images as well as expectation--maximization-like (EM-like) procedure for simultaneous parameter and partial volume estimation are reported. The robust estimators based on a pruned classification as presented here are shown to perform well even if the initial classification is of poor quality. The results obtained are comparable to those obtained using the EM-like procedure, but require considerably less computation time. Segmentation results of real data based on partial volume estimation are also reported. In addition to considering the parameter estimation problem, we discuss differences between different approximations to the complete mixel model. In summary, the proposed TMCD method allows for the accurate, robust, and efficient estimation of partial volume model parameters, which is crucial to a variety of brain MRI data analysis procedures such as the accurate estimation of tissue volumes and the accurate delineation of the cortical surface.

Artifacts↗
PubMed2004

Comparing extent of activation: a robust permutation approach.

The number of contiguous voxels activated in a brain image can differ between groups or conditions even though the amplitude of activation does not markedly differ. Existing techniques test for differences in amplitude given that extent (number of contiguous voxels) exceeds some threshold. We present a technique that tests for differences in extent of activation given that amplitude of activation exceeds some threshold. The technique was motivated by apparent differences in extent of regional cerebral blood flow (rCBF) between hypertensive and normotensive participants performing cognitive tasks. These data are used to illustrate our test for extent of activation. We threshold the estimated parameter map for each subject, count the number of voxels exceeding the threshold over a defined region enclosing activated cortical area, and test the hypothesis of difference in the number of activated voxels between the two groups. Due to the large number of zeros resulting from the thresholding and the occurrence of extreme observations, we use a Robust permutation test [Lambert, D., 1985. Robust two-sample permutation tests. Ann. Stat., 13, 606-625], which is based on the sum of censored log-likelihood ratios. This statistic has desirable properties relative to the usual permutation test in contaminated distributions, i.e., idealized histogram with outliers, and provides an appropriate and robust test of extent of activation between conditions or groups.

Adult↗