The Alopex process: Visual receptive fields by response feedback

The determination of trigger features of single neurons in afferent pathways has been one of the central problems in sensory physiology. A novel method, called Alopex, has been developed, in which response feedback is used to construct visual patterns that optimize the responses. Data are presented which show the emergence of trigger features of cells monitored in frog visual tectum. The method is checked against results obtained by scanning the visual field with a small spot. Correlations between Alopex patterns and scan patterns are generally between 0.3 and 0.5 but may be as high as 0.9 when smoothing and/or averaging procedures are applied to the Alopex patterns. The dynamics of the Alopex process are discussed and details of the algorithms are presented. The series of experiments presented here has established the validity of the method and suggests that this approach should find wide application in receptive field studies. For that purpose data on the instrumentation and software are also presented.This research has been supported by the National Institutes of Health, under grant EY 01215     

Determination of opiates in urine by capillary electrophoresis

A method for the separation of a mixture of opiates comprising pholcodine, 6-monoacetylmorphine, morphine, heroin, codeine and dihydrocodeine by capillary electrophoresis using a running buffer of 100 mM disodium hydrogenphosphate at pH 6 is described. The characteristics of an analytical method based on this separation for the determination of these drugs following extraction from urine and using levallorphan as internal standard are reported. Detection limits in the region of 10 ng cm⁻³ are achieved when using electrokinetic injection. A comparison is made of the sensitivity and reproducibility of electrokinetic and hydrodynamic injection for these drugs. Data are presented to show the results obtained when the proposed method is applied to urine spiked with all the above opiates and also to urine from a subject following consumption of dihydrocodeine and pholcodine. The concentrations found are compared with those obtained by LC.     

Using spectrophotometry to determine in vitro turnover rates of peptides in plasma

A new method for determination of first-order elimination constants for dipeptides is presented. The peptides are hydrolysed by plasma enzymes into amino acids, and ortho-phthaldialdehyde (OPA) is used to react with free primary amino groups. The concentration of free amino groups can, thus, be followed using simple spectrophotometry. A mathematical model for the concentration of free primary amino groups with time is presented through which the elimination constant, and thus the half life, can be determined by curve fitting. The method is applied to inhibitors of angiotensin-converting enzyme derived from the primary structure of milk proteins. The results show that these dipeptides have in vitro half lives ranging from 4.3-64 min, when incubated with 50% rat plasma. This explains why these casokinins in vivo only cause a very moderate and short-lasting inhibition. The model for calculation of elimination constant is limited to dipeptides that do not contain a C-terminal proline. The derivatization method can be applied to longer peptides as a crude indicator of peptide hydrolysis, but does not allow calculation of their elimination constants per se.     

THE EFFECT OF BIASED INCLUSION OF TAXA ON THE CORRELATION BETWEEN DISCRETE CHARACTERS IN PHYLOGENETIC TREES

In a published paper, a method for testing the correlation between two discrete characters was presented and applied to test whether in butterfly larvae origins of gregariousness are concentrated to lineages with aposematic coloration. The relationship was found to be nonsignificant. However, the butterfly data on which the test was applied had been compiled in another study to investigate evolutionary sequences and was biased, because there was an overrepresentation of aposematic, as compared to cryptic, branches in the sample. In the paper presented here, aposematic and cryptic clades of the original phylogeny were resolved to the same degree, and the resulting set of branches may be regarded as unbiased with respect to the hypothesis being tested. A method for testing the contingency of states in two characters was then applied to the new data set, resulting in a highly significant relationship between origins of gregariousness and aposematic coloration. I argue that when using statistical methods on phylogenetic data, it is crucial to resolve various parts of the phylogeny to the same comparable systematic unit in order not to get a distorted sample of taxa/branches.     

Reaction Field Simulations of Monatomic and Diatomic Dipolar Fluids

Firstly, the conditions are explored for which molecular dynamics simulations yield reliable thermodynamic results when the reaction field method is applied for dipolar fluids. The influence of the system size, of the scaling method for avoiding the total energy updrift, and of the reaction field dielectric constant are studied. With appropriate conditions, the results for the Stockmayer fluid when compared to previous results show excellent agreement up to very high dipole moments. In the next step the method is applied to two-centre Lennard-Jones plus ideal axial dipole (2CLJD) molecules of elongation L = 0.505. For one state point, the influence of the molecular shape as well as of the dipolar strength on energy and pressure is studied in detail. Finally, in the project of developing a physically based equation of state for polar fluids, thermodynamic results are presented for 2CLJD fluids of elongation L = 0.505 for four different dipole moments at 29 state points in a temperature and density grid. For these 116 runs which all were performed with vectorized codes on a CYBER 205 also the uncertainties in the results are given as have been estimated from the running averages.     

A Cladistic Measure of Gene Flow Inferred from the Phylogenies of Alleles

A method for estimating the average level of gene flow among populations is introduced. The method provides an estimate of Nm, where N is the size of each local population in an island model and m is the migration rate. This method depends on knowing the phylogeny of the nonrecombining segments of DNA that are sampled. Given the phylogeny, the geographic location from which each sample is drawn is treated as multistate character with one state for each geographic location. A parsimony criterion applied to the evolution of this character on the phylogeny provides the minimum number of migration events consistent with the phylogeny. Extensive simulations show that the distribution of this minimum number is a simple function of Nm. Assuming the phylogeny is accurately estimated, this method provides an estimate of Nm that is as nearly as accurate as estimates obtained using FST and other statistics when Nm is moderate. Two examples of the use of this method with mitochondrial DNA data are presented.     

Comparison of several digital and stereological methods for estimating surface area and volume of cells studied by confocal microscopy.

BACKGROUND: The implementation of different methods for estimating the surface area and volume of cells studied by confocal microscopy was developed. The methods were compared from the point of view of their precision, applicability and efficiency. METHODS: Interactive stereological methods (spatial grid method, fakir method, Cavalieri principle) as well as automatic digital methods (digital Crofton method, voxel counting, triangulation method, iso-intensity contouring method) were considered. The methods were tested on model geometrical solids and on real volume images consisting of a stack of serial sections encompassing entire tobacco BY-2 cells or cell chains. RESULTS: It is shown that many of the studied methods are very precise when applied to cells of simple or moderately complex shapes. The automatic digital methods are fast and precise but their applicability is limited by the necessity to segment automatically the object surface and to find an optimal resolution. This limitation is not present in stereological methods which are applied interactively and thus are more time-consuming. CONCLUSIONS: The presented implementations of the fakir method and the Cavalieri principle enable interactive, unbiased and efficient estimation of the cell surface area and volume. The recommended steps for measuring the surface area and/or volume of objects studied by confocal microscopy are described.     

On statistical methods for comparison of intrasample morphometric variability: Zalavár revisited

In studies of morphology, methods for comparing amounts of variability are often important. Three different ways of utilizing determinants of covariance matrices for testing for surplus variability in a hypothesis sample compared to a reference sample are presented: an F-test based on standardized generalized variances, a parametric bootstrap based on draws on Wishart matrices, and a nonparametric bootstrap. The F-test based on standardized generalized variances and the Wishart-based bootstrap are applicable when multivariate normality can be assumed. These methods can be applied with only summary data available. However, the nonparametric bootstrap can be applied with multivariate nonnormally distributed data as well as multivariate normally distributed data, and small sample sizes. Therefore, this method is preferable when raw data are available. Three craniometric samples are used to present the methods. A Hungarian Zalavár sample and an Austrian Berg sample are compared to a Norwegian Oslo sample, the latter employed as reference sample. In agreement with a previous study, it is shown that the Zalavár sample does not represent surplus variability, whereas the Berg sample does represent such a surplus variability.     

Some statistical aspects of digital Wiener filtering and detection of prescribed frequency components in time averaging of biological signals

A statistical analysis of digital a posteriori Wiener filtering as applied to time averaging techniques for biological signals is presented. The authors show that when ap.w.f. is applied to the average signal hardly any effect can be expected, where as when applied to the individual responses, ap.w.f. improves the signal to noise ratio. The applied analysis leads to a simple test to check whether a prescribed frequency component is present.     

A multiorganism based method for Bayesian gene network estimation

The primary goal of this article is to infer genetic interactions based on gene expression data. A new method for multiorganism Bayesian gene network estimation is presented based on multitask learning. When the input datasets are sparse, as is the case in microarray gene expression data, it becomes difficult to separate random correlations from true correlations that would lead to actual edges when modeling the gene interactions as a Bayesian network. Multitask learning takes advantage of the similarity between related tasks, in order to construct a more accurate model of the underlying relationships represented by the Bayesian networks. The proposed method is tested on synthetic data to illustrate its validity. Then it is iteratively applied on real gene expression data to learn the genetic regulatory networks of two organisms with homologous genes.     

A generalized finite difference method for modeling cardiac electrical activation on arbitrary, irregular computational meshes

A generalized finite difference (GFD) method is presented that can be used to solve the bi-domain equations modeling cardiac electrical activity. Classical finite difference methods have been applied by many researchers to the bi-domain equations. However, these methods suffer from the limitation of requiring computational meshes that are structured and orthogonal. Finite element or finite volume methods enable the bi-domain equations to be solved on unstructured meshes, although implementations of such methods do not always cater for meshes with varying element topology. The GFD method solves the bi-domain equations on arbitrary and irregular computational meshes without any need to specify element basis functions. The method is useful as it can be easily applied to activation problems using existing meshes that have originally been created for use by finite element or finite difference methods. In addition, the GFD method employs an innovative approach to enforcing nodal and non-nodal boundary conditions. The GFD method performs effectively for a range of two and three-dimensional test problems and when computing bi-domain electrical activation moving through a fully anisotropic three-dimensional model of canine ventricles.     

Boundary element method analysis for the bioheat transfer equation.

In this paper, the boundary element method (BEM) approach is applied to solve the Pennes (1948) bioheat equation. The objective is to develop the BEM formulation and demonstrate its feasibility. The basic BEM formulations for the transient and steady-state cases are first presented. To demonstrate the usefulness of the BEM approach, numerical solutions for 2-D steady-state problems are obtained and compared to analytical solutions. Further, the BEM formulation is applied to model a conjugate problem for an artery imbedded in a perfused heated tissue. Analytical solution is possible when the conduction in the x-direction is negligible. The BEM and analytical results have very good agreement.     

Some aspects of obtaining rat semen by electroejaculation method

Some physical conditions of the electroejaculation method elaborated by Scott and Dziuk and Kalasiewicz and Wolański have been modyfied. A positive result of ejaculation was obtained in 92.6% of the rats examined when the electric stimuli was applied with the energy of 4--7 times lower than that used by the cited authors. The presented method may prove useful in cases when the same animal is to be used repeatedly.     

Random Leslie matrices in population dynamics

We generalize the concept of the population growth rate when a Leslie matrix has random elements (correlated or not), i.e., characterizing the disorder in the vital parameters. In general, we present a perturbative formalism to deal with linear non-negative random matrix difference equations, then the non-trivial effective eigenvalue of which defines the long-time asymptotic dynamics of the mean-value population vector state is presented as the effective growth rate. This effective eigenvalue is calculated from the smallest positive root of a secular polynomial. Analytical (exact and perturbative calculations) results are presented for several models of disorder. In particular, a 3 × 3 numerical example is applied to study the effective growth rate characterizing the long-time dynamics of a biological population model. The present analysis is a perturbative method for finding the effective growth rate in cases when the vital parameters may have negative covariances across populations.     

Unbiased estimation of evolutionary distance between nucleotide sequences

A new algorithm for estimating the number of nucleotide substitutions per site (i.e., the evolutionary distance) between two nucleotide sequences is presented. This algorithm can be applied to many estimation methods, such as Jukes and Cantor's method, Kimura's transition/transversion method, and Tajima and Nei's method. Unlike ordinary methods, this algorithm is always applicable. Numerical computations and computer simulations indicate that this algorithm gives an almost unbiased estimate of the evolutionary distance, unless the evolutionary distance is very large. This algorithm should be useful especially when we analyze short nucleotide sequences. It can also be applied to amino acid sequences, for estimating the number of amino acid replacements.      

Likelihood based observability analysis and confidence intervals for predictions of dynamic models

ABSTRACT: BACKGROUND: Predicting a system's behavior based on a mathematical model is a primary task in Systems Biology. If the model parameters are estimated from experimental data, the parameter uncertainty has to be translated into confidence intervals for model predictions. For dynamic models of biochemical networks, the nonlinearity in combination with the large number of parameters hampers the calculation of prediction confidence intervals and renders classical approaches as hardly feasible. RESULTS: In this article reliable confidence intervals are calculated based on the prediction profile likelihood. Such prediction confidence intervals of the dynamic states can be utilized for a data-based observability analysis. The method is also applicable if there are non-identifiable parameters yielding to some insufficiently specified modelpredictions that can be interpreted as non-observability. Moreover, a validation profile likelihood is introduced that should be applied when noisy validation experiments are to be interpreted. CONCLUSIONS: The presented methodology allows the propagation of uncertainty from experimental to model pre-dictions. Although presented in the context of ordinary differential equations, the concept is general and also applicable to other types of models. Matlab code which can be used as a template to implement the method is provided at http://www.fdmold.uni-freiburg.de/~ckreutz/PPL .     

Efficacy of an enzyme-linked immunosorbent assay as a diagnostic tool for schistosomiasis mansoni in individuals with low worm burden

IgM-ELISA is an immunoenzymatic method useful for detection of IgM antibodies against a fraction of Schistosoma mansoni adult worm antigen (AWA) that is soluble in trichloroacetic acid (AWA-TCA). This method was applied to three groups of individuals with different clinical and epidemiological characteristics, and the results compared with those obtained by other diagnostic methods: immunofluorescence test for detection of IgM antibodies (IgM-IFT) or IgG antibodies (IgG-IFT), ELISA for detection of IgG antibodies (IgG-ELISA), and two parasitological methods, Kato-Katz and miracidium hatching. The IgM-ELISA presented a sensitivity of 98%, when the parasitologic fecal examination was defined as reference diagnostic method, and a specificity of 98 and 97.3%, respectively for the group of clinically healthy individuals and other helminth carriers. A comparative analysis between the results of IgM-ELISA and those obtained by other serologic tests showed a good degree of agreement, with Kappa indices ranging from 0.95 to 0.98. The diagnostic efficacy of 97.8%, as determined with schistosomiasis patients with low parasitic burden, suggests the excellent performance of the IgM-ELISA and its usefulness for the diagnosis of schistosomiasis when applied in low endemic areas.     

Studies on on-line bioreactor identification. IV. Utilization of pH measurements for product estimation

Relationships between the total rate of biomass growth and the rate of ammonia addition to a fermentor for pH control are presented. These equations make use of the concept of reaction invariants and provide the additional information needed for bioreactor identification. They are especially useful when the RQ measurement is not sufficient for this purpose, such as when sensitivities arise with the measured values of the respiratory quotient or when fermentation products are formed. The cases of batch, fed-batch and continuous fermentations, forming products with or without acidic/basic properties are considered. The derived relationships were successfully tested with nonbiological acid-base continuous flow reaction systems and subsequently applied to the identification of the continuous yeast fermentation of glucose to ethanol. Results of these experimental studies are also presented.     

Nutrient dependence of phytoplankton production in brown-water lakes with special reference to Lake Päijänne

A method for predicting the mean seasonal chlorophyll a concentration, the mean seasonal in vitro phytoplankton primary productivity per unit volume, the maximum daily production per unit volume and the seasonal integral production in brown-water lakes is presented. The production values can be calculated when the mean annual concentration of total phosphorus and the mean annual colour of the water are known. This method has been developed especially for practical water pollution studies to permit rapid and inexpensive estimates of major biological consequences of changes in effluent loads. The method can be applied for brown-water lakes where phosphorus is the limiting nutrient for primary production.     

A Fault Diagnosis Methodology for Gear Pump Based on EEMD and Bayesian Network

This paper proposes a fault diagnosis methodology for a gear pump based on the ensemble empirical mode decomposition (EEMD) method and the Bayesian network. Essentially, the presented scheme is a multi-source information fusion based methodology. Compared with the conventional fault diagnosis with only EEMD, the proposed method is able to take advantage of all useful information besides sensor signals. The presented diagnostic Bayesian network consists of a fault layer, a fault feature layer and a multi-source information layer. Vibration signals from sensor measurement are decomposed by the EEMD method and the energy of intrinsic mode functions (IMFs) are calculated as fault features. These features are added into the fault feature layer in the Bayesian network. The other sources of useful information are added to the information layer. The generalized three-layer Bayesian network can be developed by fully incorporating faults and fault symptoms as well as other useful information such as naked eye inspection and maintenance records. Therefore, diagnostic accuracy and capacity can be improved. The proposed methodology is applied to the fault diagnosis of a gear pump and the structure and parameters of the Bayesian network is established. Compared with artificial neural network and support vector machine classification algorithms, the proposed model has the best diagnostic performance when sensor data is used only. A case study has demonstrated that some information from human observation or system repair records is very helpful to the fault diagnosis. It is effective and efficient in diagnosing faults based on uncertain, incomplete information.