Epithelial transport parameters: an analysis of experimental strategies

A set of experiments was simulated on a computer version of the Koefoed-Johnsen & Ussing model for high-resistance epithelia. The results obtained were analysed according to procedures commonly applied to the analyses of experimental data and interpreted in terms of the model parameters. Although the computer model encodes a stoichiometry of 3:2 for Na-K exchange through the Na pump, the simulation of published experimental procedures yields different figures in almost every case. We show that ENa as originally defined by Ussing & Zerahn (Acta physiol. scand. 23, 110-127 (1951)) and as obtained from flux-ratio experiments has different values under different experimental conditions with unchanged system parameters and that it is distinct from ENa measured by other methods. We also show that unless the pump is saturated with internal Na an increase in the rate of pumping cannot cause a substantial increase in the rate of transepithelial Na transport.     

Relax and refill: xylem rehydration prior to hydraulic measurements favours embolism repair in stems and generates artificially low PLC values

Diurnal changes in percentage loss of hydraulic conductivity (PLC), with recorded values being higher at midday than on the following morning, have been interpreted as evidence for the occurrence of cycles of xylem conduits' embolism and repair. Recent reports have suggested that diurnal PLC changes might arise as a consequence of an experimental artefact, that is, air entry into xylem conduits upon cutting stems, even if under water, while under substantial tension generated by transpiration. Rehydration procedures prior to hydraulic measurements have been recommended to avoid this artefact. In the present study, we show that xylem rehydration prior to hydraulic measurements might favour xylem refilling and embolism repair, thus leading to PLC values erroneously lower than those actually experienced by transpiring plants. When xylem tension relaxation procedures were performed on stems where refilling mechanisms had been previously inhibited by mechanical (girdling) or chemical (orthovanadate) treatment, PLC values measured in stems cut under native tension were the same as those measured after sample rehydration/relaxation. Our data call for renewed attention to the procedures of sample collection in the field and transport to the laboratory, and suggest that girdling might be a recommendable treatment prior to sample collection for PLC measurements.     

(An algorithm for determining values of parameters of the Gompertz growth function)]

In the literature some attempts were made to analyse and to construct models for biological growth processes and to describe the quantitative aspects of a growth characteristic's changes in time using the Gompertz' function y=aexp(-exp(b--ct)). In this paper differential equations are derived having the Gompertz' function as solution. The goodness of fit after adjusting a chosen analytical expression to the courses of measured values is able to give hints at the reliability of that expression as a true model. This possibility of verification was hardly practiced in past because of lacking in proper numerical procedures for performing the nonlinear regression. An ALGOL program for iterative adjusting the parameters of the GOMPERTZ' function (with or without a constant term) to measured values is given in an appendix of the present paper. Starting values for the nonlinear parameters b and c will be evaluated by Internal Least Squares using one of the derived differential equations. For this algorithm an ALGOL program is given in the appendix too. The growth of human embryo serves as an example to demonstrate the numerical procedures and related programs for evaluating the starting values of the parameters and for their iterative improvement until reaching a minimum for the remainding variance between calculated and measured courses.     

The generality of empirical and theoretical explanations of behavior

For theoretical explanations of data, parameter values estimated from a single dependent measure from one procedure are used to predict alternative dependent measures from many procedures. Theoretical explanations were compared to empirical explanations of data in which known functions and principles were used to fit only selected dependent measures. The comparison focused on the ability of theoretical and empirical explanations to generalize across samples of the data, across dependent measures of behavior, and across different procedures. Rat and human data from fixed-interval and peak procedures, in which principles (e.g., scalar timing) are well known, were described and fit by a theory with independent modules for perception, memory, and decision. The theoretical approach consisted of fitting closed-form equations of the theory to response rate gradients calculated from the data, simulating responses using parameter values previously estimated, and comparing theoretical predictions with dependent measures not used to estimate parameters. Although the empirical and theoretical explanations provided similar fits to the response rate gradients that generalized across samples and had the same number of parameters, only the theoretical explanation generalized across procedures and dependent measures.     

A new framework for the estimation of control parameters in metabolic pathways using lin-log kinetics.

The control properties of biochemical pathways can be described by control coefficients and elasticities, as defined in the framework of metabolic control analysis. The determination of these parameters using the traditional metabolic control analysis relationships is, however, limited by experimental difficulties (e.g. realizing and measuring small changes in biological systems) and lack of appropriate mathematical procedures (e.g. when the more practical large changes are made). In this paper, the recently developed lin-log approach is proposed to avoid the above-mentioned problems and is applied to estimate control parameters from measurements obtained in steady state experiments. The lin-log approach employs approximative linear-logarithmic kinetics parameterized by elasticities and provides analytical solutions for fluxes and metabolite concentrations when large changes are made. Published flux and metabolite concentration data are used, obtained from a reconstructed section of glycolysis converting 3-phosphoglycerate to pyruvate [Giersch, C. (1995) Eur. J. Biochem. 227, 194-201]. With the lin-log approach, all data from different experiments can be combined to give realistic elasticity and flux control coefficient estimates by linear regression. Despite the large changes, a good agreement of fluxes and metabolite concentrations is obtained between the measured and calculated values according to the lin-log model. Furthermore, it is shown that the lin-log approach allows a rigorous statistical evaluation to identify the optimal reference state and the optimal model structure assumption. In conclusion, the lin-log approach addresses practical problems encountered in the traditional metabolic control analysis-based methods by introducing suitable nonlinear kinetics, thus providing a novel framework with improved procedures for the estimation of elasticities and control parameters from large perturbation experiments.     

Incorporating data received after a sequential trial has stopped into the final analysis: implementation and comparison of methods

In a sequential clinical trial, accrual of data on patients often continues after the stopping criterion for the study has been met. This is termed "overrunning." Overrunning occurs mainly when the primary response from each patient is measured after some extended observation period. The objective of this article is to compare two methods of allowing for overrunning. In particular, simulation studies are reported that assess the two procedures in terms of how well they maintain the intended type I error rate. The effect on power resulting from the incorporation of "overrunning data" using the two procedures is evaluated.     

DNA fingerprinting data and the problem of non-independence among pairwise comparisons

Multilocus DNA fingerprinting is commonly used to assess genetic similarity within and between geographically disjunct populations. Typically, the proportion of DNA fingerprinting bands shared between two individuals ( S _XY) is calculated for all possible pairwise comparisons and the resulting data analyzed parametrically to test differences in mean band-sharing among groups. The degree to which covariation among interdependent S _XY values ( S _ab - S _bc) biases the analyses is often unknown. Here, we assess the extent of covariation in four DNA fingerprinting studies and evaluate the effectiveness of two corrective procedures, a permutation test and a subsampling routine using only independent pairwise comparisons drawn without replacement from the overall data. Covariation among interdependent S _XY values was significantly greater than zero in every data set examined, including those from a bee, a rodent, and two passerine birds. Permutation tests did not correct for interdependence and yielded significance values nearly identical to those derived from uncorrected parametric procedures. In contrast, the subsampling procedure yielded corrected estimates of the standard error that were two to four times larger than those derived parametrically. As a result, comparisons that were significant using parametric tests were either non-significant or only marginally significant with the subsampling routine. We conclude that interdependence among S _XY values poses a substantial obstacle to hypothesis testing that must be addressed in future studies.     

On the analysis of circular dichroic spectra of proteins.

A new method is presented for analyzing circular dichroism spectra. The method employs integrals over the data and calculates the alpha-helical, beta-sheet, and random coil content of the proteins from such integrals. It is shown that the analyzed alpha-helical content is usually reliable to within 5%, beta-sheet values are somewhat less reliable, and random coil values are least reliable. Curve fitting techniques are shown to be misleading. The method has a number of advantages over existing procedures.     

Typical values related to the complexity of interventional treatment of acute ischemic stroke

Background and PurposeInterventional Neuroradiology (INR) procedures are often complex, requiring prolonged high-dose exposures. This leads to increased radiation exposure to both patient and operating staff. The purpose of this study is to identify parameters related to the complexity of acute ischemic stroke (AIS) procedures that increase patient exposure and derive DRLs according to ICRP 135.MethodsData from 145 patients treated for AIS between 2017 and 2019 in a Hub Stroke center were retrospectively analyzed. Dosimetric parameters, demographic and clinical data were collected for each patient. The INR operator and the fluoroscopy system used were included.ResultsA multivariable analysis was performed to identify which parameters significantly influence the dosimetric data. Thrombus location and the use of stent retriever were noted as the most likely parameters of complex INR procedures. Male sex is an indicator of complex procedure only with regards to the Kerma area product and the air kerma. Patient age significantly affects the exposure time alone. Senior or more experienced operator’s data demonstrated reduced patient's exposure time and therefore the KAP and Kar values. The type of X-ray equipment influenced the outcome of the procedure in terms of number of images acquired. Typical values obtained are 168 Gycm², 0.68 Gy, 19 min and 181 images.ConclusionTypical values derived in this study promote patient dose optimization, when considering the complexity of INR procedures. The clinical variables related to the complexity of procedure that mainly affect the dosimetric data in our experience are thrombus location and use of stent retrievers.     

Nonparametric analysis of covariance for comparing change in randomized studies with baseline values subject to error

Change from baseline to a follow-up examination can be compared among two or more randomly assigned treatment groups by using analysis of variance on the change scores. However, a generally more sensitive (powerful) test can be performed using analysis of covariance (ANOVA) on the follow-up data with the baseline data as a covariate. This approach is not without potential problems, though. The assumption of ordinary ANCOVA of normally distributed errors is speculative for many variables employed in biomedical research. Furthermore, the baseline values are inevitably random variables and often are measured with error. This report investigates, in this situation, the validity and relative power of the ordinary ANCOVA test and two asymptotically distribution-free alternative tests, one based on the rank transformation and the other based on the normal scores transformation. The procedures are illustrated with data from a clinical trial. Normal and several nonnormal distributions, as well as varying degree of variable error, are studied by Monte Carlo methods. The normal scores test is generally recommended for statistical practice.     

Pitfalls of hypothesis tests and model selection on bootstrap samples: Causes and consequences in biometrical applications

The bootstrap method has become a widely used tool applied in diverse areas where results based on asymptotic theory are scarce. It can be applied, for example, for assessing the variance of a statistic, a quantile of interest or for significance testing by resampling from the null hypothesis. Recently, some approaches have been proposed in the biometrical field where hypothesis testing or model selection is performed on a bootstrap sample as if it were the original sample. P‐values computed from bootstrap samples have been used, for example, in the statistics and bioinformatics literature for ranking genes with respect to their differential expression, for estimating the variability of p‐values and for model stability investigations. Procedures which make use of bootstrapped information criteria are often applied in model stability investigations and model averaging approaches as well as when estimating the error of model selection procedures which involve tuning parameters. From the literature, however, there is evidence that p‐values and model selection criteria evaluated on bootstrap data sets do not represent what would be obtained on the original data or new data drawn from the overall population. We explain the reasons for this and, through the use of a real data set and simulations, we assess the practical impact on procedures relevant to biometrical applications in cases where it has not yet been studied. Moreover, we investigate the behavior of subsampling (i.e., drawing from a data set without replacement) as a potential alternative solution to the bootstrap for these procedures.     

Evaluation of different staining procedures for the quantification of fibroblasts cultured in 96-well plates.

Comparison of published methods for the quantification of adherent cell numbers by the measurement of absorbance of bound stain indicates a wide variation in their sensitivity. This study aimed at comparing the sensitivities of five different staining procedures (Coomassie brilliant blue G in perchloric acid, Coomassie brilliant blue G in phosphoric acid, methylene blue, crystal violet, and toluidine blue) applied to three separate types of cultured fibroblasts (3T3 cells, Vero cells, and human gingival fibroblasts) at concentrations from 0.125 x 10(4) to 10 x 10(4) per well in 96-well microplates. Absorbance values of Coomassie blue-stained cells were measured in situ. Those of the remaining cells were measured after solubilization of the dye with 1% sodium dodecyl sulfate. All absorbance values were measured using an Elisa reader at 620 or 570 nm for crystal violet. The relationship between cell number and absorbance over the entire cell concentration range was best fitted with quadratic regression analysis, in contrast with the linear relationship described elsewhere. The order of sensitivity of the staining procedures was the same for each cell type: Coomassie blue in perchloric acid less than Coomassie blue in phosphoric acid less than methylene blue less than crystal violet less than toluidine blue. With the latter two stains absorbance values began to plateau at approximately 8 x 10(4) cells per well. However, staining with Coomassie blue in perchloric acid and methylene blue resulted in an almost linear relationship between cell number and absorbance over the entire concentration range tested.(ABSTRACT TRUNCATED AT 250 WORDS)     

Procedures in the biochemical estimation of age of vertebrates

The most accurate method known to data for estimating age of wild vertebrates involves biochemical assay of eye lens proteins. Laboratory procedures that may be unfamiliar to many ecologists are described in detail. The method is based on precise changes in the amount of insoluble lens protein, and consists of two procedures: obtaining the appropriate lens fraction, and quantitatively analyzing its protein composition. Lenses are homogenized, and the insoluble fraction isolated by centrifugation. Protein content is measured colorimetrically by using the Lowry test. Instructions are given for single and double-beam spectrophotometers.     

Inherent bias toward the null hypothesis in conventional multipoint nonparametric linkage analysis

Traditional nonparametric "multipoint" statistical procedures have been developed for assigning allele-sharing values at a locus of interest to pairs of relatives for linkage studies. These procedures attempt to accommodate a lack of informativity, nongenotyped loci, missing data, and related issues concerning the genetic markers used in a linkage study. However, such procedures often cannot overcome these phenomena in compelling ways and, as a result, assign relevant relative pairs allele-sharing values that are "expected" for those pairs. The practice of assigning expected allele-sharing values to relative pairs in the face of a lack of explicit allele-transmission information can bias traditional nonparametric linkage test statistics toward the null hypothesis of no locus effect. This bias is due to the use of expected values, rather than to a lack of information about actual allele sharing at relevant marker loci. The bias will vary from study to study on the basis of the DNA markers, sample size, relative-pair types, and pedigree structures used, but it can be extremely pronounced and could contribute to a lack of consistent success in the application of traditional nonparametric linkage analyses to complex human traits and diseases. There are several potential ways to overcome this problem, but their foundations deserve greater research. We expose many of the issues concerning allele sharing with data from a large affected-sibling-pair study investigating the genetic basis of autism.     

The relationship between mean channel selection and the calculated coefficient of variation

Calculated coefficients of variation (CV) taken from the quotient of the standard deviation (S.D.) and the mean value of measured distributions are often used as an indicator of system performance in linear flow cytometry (FCM). The ability of the calculated CV to estimate the true CV of the underlying experiment before grouping (channelization) is dependent on the relationship between the width of the data channels and the magnitude of the S.D. of the measured distribution. When the channel width is equal to the S.D. of a distribution, the calculated CV is approximately 20% larger than the true CV of an experiment. By the time the S.D. is only one-half of a channel width, the calculated CV is unreliable. When the distribution S.D. is narrower than a channel's width, small changes in the distribution mean value will cause large variations in the calculated CV. As the true CV decreases, the calculation must be made with higher mean channel values. This dependence of calculated CV accuracy upon the relationship between S.D. and channel width places limitations upon mean channel selection that must be considered when using CV calculations for evaluating system performance, especially when looking for small improvements during optical alignment procedures. When an instrument is assumed to have a constant CV and the data are collected linearly, it is possible to improve the CV estimation accuracy by placing distributions in higher-numbered channels.(ABSTRACT TRUNCATED AT 250 WORDS)     

Estimating transfer parameters in the absence of data

The calculation of transfer of radionuclides from the abiotic to the biotic environment is a well-established practice in radiological assessments. Concentration ratios provide simple means to estimate radionuclide activity in biota, from measured (or estimated) radionuclide concentrations in either a food source or an abiotic component such as soil or water. They are typically reported by element, and data compilations may include information such as soil type (e.g., sand, loam, clay) and species. The data may be for multiple species at a single location, single species at multiple locations, or represent compilations from multiple sources. Recently published guidance suggests that estimates are best made using data from the same ecosystem. This paper examines this recent guidance, in the context of using measured data from within a single ecosystem and comparing results to more generic values. Results suggest that generic values may be an adequate substitute for site-specific information. It illustrates how ionic potential may be used as an alternative to group chemical properties in estimating transfer factors. Lastly, limited evidence is found to support the concept of allometric scaling functions for elemental concentrations in plants.     

Comparison of methods of expression and measurement of cation exchange capacity of plant roots

Summary Cation exchange capacity (CEC) of roots of fifteen genetically different tea clones was measured and the values were expressed on surface area and weight basis. The precision of the two methods is almost identical. The weight basis is, however, preferred as it is more convenient and less time consuming.In another experiment. CEC was determined separately on whole root system and on fractionated root segments (i.e. white and brown root portions). Highly significant and positive relationship between CEC values obtained with whole roots and those calculated from the fractionated root segments indicates that CEC can be more successfully measured on whole roots without sacrificing accuracy. Practical implications of both the procedures in root CEC-nutrient uptake relationship study was discussed.     

Sedimentation equilibrium of proteins in density gradients.

The technique of sedimentation equilibrium in density gradients in the analytical ultracentrifuge has been applied to the study of proteins. A variety of effects and procedures including the use of density marker beads, the effects of pressure on buoyant density and pH, and the calculation of compositional density gradient proportionality constants and density--refractive index relations have been developed. The buoyant densities of twenty-four proteins have been measured and hydration values computed. The buoyant titrations of six proteins have been measured. These data have been interpreted in terms of the buoyant titrations which have been obtained for six ionizable homopolypeptides, five copolypeptides, two non-ionizable homopolypeptides and three chemically modified proteins. Spectropolarimetry and potentiometric titrations were employed to further interpret these data. Approximate values for dissociation constants, numbers of ionizable residues, and the nature of ions bound or dissociated upon ionization have been obtained. The relation between potentiometric and buoyant titrations and the use of density gradient centrifugation as a probe for protein structure have been explored.