On the statistical evaluation of adherence assays

Parametric (unpaired t-test) and non-parametric (Mann-Whitney U-test) methods have been used in the evaluation of adherence assays on the non-antibiotic antimicrobial agent, Taurolin. In all but one case, where the anti-adherence effect was known to be marginal, both statistical methods gave similar results although there were some minor differences in the levels of significance achieved. The effect of the agent on the deviation of adherence data from normality was quantified by calculation of the skewness coefficient for each data set. A significant anti-adherence effect appears to result in a decrease in the skewness of the adherence assay data. It was concluded that either parametric or non-parametric statistical evaluation of adherence assay data is valid for large numbers of observations. In future studies of this type it is suggested that attention should also be given to the effect of the anti-adherence agent on the deviation of adherence data from normality as denoted by the skewness coefficient.     

Reduced adherence of micro-organisms to human mucosal epithelial cells following treatment with Taurolin, a novel antimicrobial agent

Taurolin, a non-antibiotic antimicrobial agent, significantly reduced the adherence of buccal and vaginal strains of Candida albicans blastospores and urine isolates of Escherichia coli and Staphylococcus saprophyticus to epithelial cells. Light microscopy and radio-isotopic counting methods were used to quantify the adherence of the micro-organisms to either uroepithelial or buccal epithelial cells. A maximum reduction in adherence of approximately 65% was obtained. The anti-adherence capacity was time-dependent, requiring a contact time of 30 min to achieve maximum effect. Taurolin at sub-minimum inhibitory concentrations (MIC) significantly reduced the adherence of Candida and E. coli. A concentration slightly higher than the MIC was required for Staph. saprophyticus. Treatment of either epithelial cells or micro-organisms with Taurolin resulted in reduced adherence of microorganisms.     

Reduced adherence of micro-organisms to human mucosal epithelial cells following treatment with Taurolin, a novel antimicrobial agent

Taurolin, a non-antibiotic antimicrobial agent, significantly reduced the adherence of buccal and vaginal strains of Candida albicans blastospores and urine isolates of Escherichia coli and Staphylococcus saprophyticus to epithelial cells. Light microscopy and radio-isotopic counting methods were used to quantify the adherence of the micro-organisms to either uroepithelial or buccal epithelial cells. A maximum reduction in adherence of approximately 65% was obtained. The anti-adherence capacity was time-dependent, requiring a contact time of 30 min to achieve maximum effect. Taurolin at sub-minimum inhibitory concentrations (MIC) significantly reduced the adherence of Candida and E. coli. A concentration slightly higher than the MIC was required for Staph. saprophyticus. Treatment of either epithelial cells or micro-organisms with Taurolin resulted in reduced adherence of microorganisms.     

Decrease in adherence of bacteria and yeasts to human mucosal epithelial cells by noxythiolin in vitro

Adherence of buccal and vaginal isolates of Candida albicans to buccal epithelial cells and the adherence of urine isolates of Escherichia coli and Staphylococcus saprophyticus to uroepithelial cells was quantified by light microscopy. The antimicrobial agent noxythiolin reduced the adherence of these micro-organisms in both exponential and stationary growth phases. Adherence of both the blastospore and pseudohyphal forms of C. albicans was reduced. Treatment of epithelial cells and/or micro-organisms with noxythiolin resulted in decreased adherence. No anti-adherence effect was observed with formaldehyde and N-methylthiourea, the degradative products of noxythiolin.     

Stabilization Coefficient of Random Variable

Coefficient of variation, standard deviation divided by mean, has some essential defects. Its density, expectation and variance are too complex to make the statistical inference for such a coefficient. The definition of stabilization coefficient is just the reciprocal of variation coefficient, mean divided by standard deviation. Such a coefficient has a simple expectation and a simple variance, and is an asymptotically unbiased estimator and a consistent estimator of its true value. Furthermore, coefficient of stabilization has an asymptotic normality. Due to its statistical advantages, coefficient of stabilization is easy to be tested statistically. In some applied fields, usually, there is an increasing standard deviation accompanying an increasing mean. Coefficient of stabilization can be practically used for some comparison studies in such fields. Illustrations about comparing microorganism strains are given in this paper. The robustness of stabilization coefficient is satisfactory.     

Statistical methods for short-term tests in genetic toxicology: the first fifteen years.

Short-term tests (STTs) for detecting and assessing genotoxic or mutagenic effects have catalyzed the development of biostatistical methods for more than one decade. Most notably, the Ames Salmonella/microsome assay created statistical methodology with a range of applications going beyond genotoxicity. Early approaches with parametric statistical methods appeared to be insufficient and have been replaced by non-parametric ones requiring less restrictive distributional assumptions. There have also been successful attempts to use biomathematical models for establishing dose-response relationships. Overdispersion has been recognized as a major problem for the evaluation of mutagenic count data and methods to cope with it have became available. A theory of generalized linear modelling is emerging to combine dose-response modeling with much less restrictive distributional assumptions, while allowing the inclusion of concomitant factors arising from the experimental conditions. The methodological survey below reviews the present state of this development and is intended to promote further research into biostatistical issues and methods of analysis. Appropriate methods for the design and analysis of STTs are discussed. The progress for the Ames assay was only partially transmitted to the analysis of the large number of other short-term assays. Several such assays are reviewed with respect to their present state of statistical evaluation.     

Economic values under inappropriate normal distribution assumptions

The objectives of this study were to quantify the errors in economic values (EVs) for traits affected by cost or price thresholds when skewed or kurtotic distributions of varying degree are assumed to be normal and when data with a normal distribution is subject to censoring. EVs were estimated for a continuous trait with dichotomous economic implications because of a price premium or penalty arising from a threshold ranging between −4 and 4 standard deviations from the mean. In order to evaluate the impacts of skewness, positive and negative excess kurtosis, standard skew normal, Pearson and the raised cosine distributions were used, respectively. For the various evaluable levels of skewness and kurtosis, the results showed that EVs can be underestimated or overestimated by more than 100% when price determining thresholds fall within a range from the mean that might be expected in practice. Estimates of EVs were very sensitive to censoring or missing data. In contrast to practical genetic evaluation, economic evaluation is very sensitive to lack of normality and missing data. Although in some special situations, the presence of multiple thresholds may attenuate the combined effect of errors at each threshold point, in practical situations there is a tendency for a few key thresholds to dominate the EV, and there are many situations where errors could be compounded across multiple thresholds. In the development of breeding objectives for non-normal continuous traits influenced by value thresholds, it is necessary to select a transformation that will resolve problems of non-normality or consider alternative methods that are less sensitive to non-normality.     

A robust multiple-locus method for quantitative trait locus analysis of non-normally distributed multiple traits

Linear regression-based quantitative trait loci/association mapping methods such as least squares commonly assume normality of residuals. In genetics studies of plants or animals, some quantitative traits may not follow normal distribution because the data include outlying observations or data that are collected from multiple sources, and in such cases the normal regression methods may lose some statistical power to detect quantitative trait loci. In this work, we propose a robust multiple-locus regression approach for analyzing multiple quantitative traits without normality assumption. In our method, the objective function is least absolute deviation (LAD), which corresponds to the assumption of multivariate Laplace distributed residual errors. This distribution has heavier tails than the normal distribution. In addition, we adopt a group LASSO penalty to produce shrinkage estimation of the marker effects and to describe the genetic correlation among phenotypes. Our LAD-LASSO approach is less sensitive to the outliers and is more appropriate for the analysis of data with skewedly distributed phenotypes. Another application of our robust approach is on missing phenotype problem in multiple-trait analysis, where the missing phenotype items can simply be filled with some extreme values, and be treated as outliers. The efficiency of the LAD-LASSO approach is illustrated on both simulated and real data sets.     

Adherence of Staphylococcus aureus to cell monolayers

Adherence of four strains of Staphylococcus aureus to eukaryotic cell monolayers was assayed with [3H]-thymidine labelled bacterial cells and the results were analysed by non-parametric statistical tests. Adherence to primary (human mesothelial) and semi-continuous (human embryonic lung) cell monolayers was significantly better than to continuous cell lines (HEp2, HeLa and Vero). HEp2 cell monolayers provided the most reliable assay substrate of the continuous cell lines tested. Variation occurred between bacterial culture batches but the assay measured significant differences between adhesion levels of the strains and distinguished between high level (RN92, 8325-4) and low level (Wood46, ISP458) adhering strains. Adherence to different batches of cell monolayers also varied but relative adherence values for strains were similar and the ranking of strains according to adhesion values was unchanged. Potential adhesion mediators have been monitored for their effect on adhesion of a highly adherent strain (RN92) to HEp2 monolayers. Fibronectin, protein A and anti-protein A did not significantly affect adhesion. Lipoteichoic acid caused a significant inhibition of adhesion. With critical statistical analysis to accommodate inherent variations, this assay provides a useful model to study factors involved in adherence of Staph. aureus to eukaryotic cells.     

Screening of knee-joint vibroarthrographic signals using probability density functions estimated with Parzen windows

Pathological conditions of knee joints have been observed to cause changes in the characteristics of vibroarthrographic (VAG) signals. Several studies have proposed many parameters for the analysis and classification of VAG signals; however, no statistical modeling methods have been explored to analyze the distinctions in the probability density functions (PDFs) between normal and abnormal VAG signals. In the present work, models of PDFs were derived using the Parzen-window approach to represent the statistical characteristics of normal and abnormal VAG signals. The Kullback-Leibler distance was computed between the PDF of the signal to be classified and the PDF models for normal and abnormal VAG signals. Additional statistical measures, including the mean, standard deviation, coefficient of variation, skewness, kurtosis, and entropy, were also derived from the PDFs obtained. An overall classification accuracy of 77.53%, sensitivity of 71.05%, and specificity of 82.35% were obtained with a database of 89 VAG signals using a neural network with radial basis functions with the leave-one-out procedure for cross validation. The screening efficiency was derived to be 0.8322, in terms of the area under the receiver operating characteristics curve.     

林木个体大小不一致性指标对人工林间伐方式的即时性响应

以广西14年生杉木和马尾松人工林为对象,设同一疏伐强度的下层疏伐、上层疏伐、机械疏伐和干扰树间伐4种处理,分别用标准差、变异系数、偏度、Gini系数、库兹涅茨系数和洛伦茨不对称系数6种指标对4种间伐方式下采伐前后林木个体大小差异进行评价.结果表明: 与间伐前相比,马尾松和杉木人工林下层疏伐或上层疏伐后,林木个体材积的标准差、变异系数、Gini系数和库兹涅茨系数均变小,偏度变大;干扰树间伐后标准差、变异系数、Gini系数和库兹涅茨系数均变大,偏度则不一定.马尾松林和杉木林下层疏伐后洛伦茨不对称系数变大,上层疏伐或干扰树间伐后则变小.机械疏伐后各指标无明显变化规律.干扰树间伐后林木个体大小差异性增加,上层疏伐和下层疏伐后林木个体大小差异性减小.洛伦茨曲线、Gini系数和洛伦茨不对称系数均能较好地反映林木个体大小不一致性,可以进行不同林分间个体差异程度静态和动态比较,较好地反映不同间伐方式引起的林木个体差异.洛伦茨不对称系数可以判断林木个体大小不一致性的来源是大树还是小树.近自然森林经营中干扰树间伐措施可以在减小目标树竞争压力的同时拉大林木个体大小差距,有助于保持目标树在林分中的优势地位.
     

Statistical treatment of VAM infection data

Summary The amount of vesicular-arbuscular mycorrhizal (VAM) infection, when expressed as length of infected roots, is commonly quite variable among replicate pots within an experimental treatment. In this paper we show that frequency distributions of VAM infection parameters are often non-normal in form and may follow the negative binomial, a distribution commonly associated with aggregated organisms in nature. The lack of normality means that statistical procedures should either be non-parametric or should include data transformations.     

Response definition criteria for ELISPOT assays revisited

No consensus has been reached on how to determine if an immune response has been detected based on raw data from an ELISPOT assay. The goal of this paper is to enable investigators to understand and readily implement currently available methods for response determination. We describe empirical and statistical approaches, identifying the strengths and limitations of each approach to allow readers to rationally select and apply a scientifically sound method appropriate to their specific laboratory setting. Five representative approaches were applied to data sets from the CIMT Immunoguiding Program and the response detection and false positive rates were compared. Simulation studies were also performed to compare empirical and statistical approaches. Based on these, we recommend the use of a non-parametric statistical test. Further, we recommend that six medium control wells or four wells each for both medium control and experimental conditions be performed to increase the sensitivity in detecting a response, that replicates with large variation in spot counts be filtered out, and that positive responses arising from experimental spot counts below the estimated limit of detection be interpreted with caution. Moreover, a web-based user interface was developed to allow easy access to the recommended statistical methods. This interface allows the user to upload data from an ELISPOT assay and obtain an output file of the binary responses.     

Guidelines for the design and statistical analysis of experiments in papers submitted to ATLA

In vitro experiments need to be well designed and correctly analysed if they are to achieve their full potential to replace the use of animals in research. An "experiment" is a procedure for collecting scientific data in order to answer a hypothesis, or to provide material for generating new hypotheses, and differs from a survey because the scientist has control over the treatments that can be applied. Most experiments can be classified into one of a few formal designs, the most common being completely randomised, and randomised block designs. These are quite common with in vitro experiments, which are often replicated in time. Some experiments involve a single independent (treatment) variable, while other "factorial" designs simultaneously vary two or more independent variables, such as drug treatment and cell line. Factorial designs often provide additional information at little extra cost. Experiments need to be carefully planned to avoid bias, be powerful yet simple, provide for a valid statistical analysis and, in some cases, have a wide range of applicability. Virtually all experiments need some sort of statistical analysis in order to take account of biological variation among the experimental subjects. Parametric methods using the t test or analysis of variance are usually more powerful than non-parametric methods, provided the underlying assumptions of normality of the residuals and equal variances are approximately valid. The statistical analyses of data from a completely randomised design, and from a randomised-block design are demonstrated in Appendices 1 and 2, and methods of determining sample size are discussed in Appendix 3. Appendix 4 gives a checklist for authors submitting papers to ATLA.     

Clustering and Power Transformation Based Methods for the Departure of Normality in Korean Soil Investigation Data

The Korean guidelines developed by the Ministry of Environment for soil investigations do not seriously take into account statistical characteristics of collected data and statistical assumptions required for the methods applied. In this article, we point out the statistical omissions in the Korean guidelines and propose some supplements to them. Systematic sampling is recommended, since systematic sampling raises sample representativeness and provides a more efficient allocation of resources that lead to cost-savings. The type of statistical inference should be determined according to the objective of the investigation and the presence of normality. We provide a diagram for selecting an appropriate type of inference. We also introduce power transformation and propose a clustering-based stratification method for improving the accuracy of analysis and the normality condition of data. Both methods are illustrated with real datasets collected from a northern region of South Korea. One of those non-normal datasets was normalized simply by applying power transformation. The other needed to be clustered into two heterogeneous groups by our proposed method before transformation, which enables applying normality-based methods to the data.     

Bayesian analysis of multivariate mixed models for a prospective cohort study using skew‐elliptical distributions

Classical multivariate mixed models that acknowledge the correlation of patients through the incorporation of normal error terms are widely used in cohort studies. Violation of the normality assumption can make the statistical inference vague. In this paper, we propose a Bayesian parametric approach by relaxing this assumption and substituting some flexible distributions in fitting multivariate mixed models. This strategy allows for the skewness and the heavy tails of error‐term distributions and thus makes inferences robust to the violation. This approach uses flexible skew‐elliptical distributions, including skewed, fat, or thin‐tailed distributions, and imposes the normal model as a special case. We use real data obtained from a prospective cohort study on the low back pain to illustrate the usefulness of our proposed approach.     

Adherence of Staphylococcus aureus to cell monolayers

W yatt , J.E., P oston , S.M. & N oble , W.C. 1990. Adherence of Staphylococcus aureus to cell monolayers. Journal of Applied Bacteriology 69 , 834–844.
Adherence of four strains of Staphylococcus aureus to eukaryotic cell monolayers was assayed with [³H]-thymidine labelled bacterial cells and the results were analysed by non-parametric statistical tests. Adherence to primary (human mesothelial) and semi-continuous (human embryonic lung) cell monolayers was significantly better than to continuous cell lines (HEp2, HeLa and Vero). HEp2 cell monolayers provided the most reliable assay substrate of the continuous cell lines tested. Variation occurred between bacterial culture batches but the assay measured significant differences between adhesion levels of the strains and distinguished between high level (RN92, 8325–4) and low level (Wood46, ISP458) adhering strains. Adherence to different batches of cell monolayers also varied but relative adherence values for strains were similar and the ranking of strains according to adhesion values -was unchanged.
Potential adhesion mediators have been monitored for their effect on adhesion of a highly adherent strain (RN92) to HEp2 monolayers. Fibronectin, protein A and anti-protein A did not significantly affect adhesion. Lipoteichoic acid caused a significant inhibition of adhesion. With critical statistical analysis to accommodate inherent variations, this assay provides a useful model to study factors involved in adherence of Staph. aureus to eukaryotic cells.     

A Simple Statistical Parameter for Use in Evaluation and Validation of High Throughput Screening Assays

The ability to identify active compounds (3hits2) from large chemical libraries accurately and rapidly has been the ultimate goal in developing high-throughput screening (HTS) assays. The ability to identify hits from a particular HTS assay depends largely on the suitability or quality of the assay used in the screening. The criteria or parameters for evaluating the 3suitability2 of an HTS assay for hit identification are not well defined and hence it still remains difficult to compare the quality of assays directly. In this report, a screening window coefficient, called 3Z-factor,2 is defined. This coefficient is reflective of both the assay signal dynamic range and the data variation associated with the signal measurements, and therefore is suitable for assay quality assessment. The Z-factor is a dimensionless, simple statistical characteristic for each HTS assay. The Z-factor provides a useful tool for comparison and evaluation of the quality of assays, and can be utilized in assay optimization and validation.     

Reduced adherence and inhibition of hyphal development of Candida albicans by the antimicrobial agent polynoxylin

Polynoxylin (Anaflex R) was investigated for antimicrobial activities ancillary to its known cidal and static effects. Significant reductions in adherence of Candida albicans blastospores (oral strain) to human buccal epithelial cells were observed following polynoxylin treatment. The anti-adherence activity was concentration and time-dependent. Treatment of the epithelial cells did not result in significant reductions in adherence. Polynoxylin was also shown to inhibit the germination and hyphal development of C. albicans.     

A practical validation approach for virus titer testing of avian infectious bursal disease live vaccine according to current regulatory guidelines

The method for virus titer determination of avian infectious bursal disease (IBD) live vaccine, developed long before regulatory validation guidelines is a cell culture based biological assay intended for use in vaccine release testing.The aim of our study was to perform a validation, based on fit-for-purpose principle, of an old 50% tissue culture infectious dose (TCID₅₀) method according to Guidelines of the International Cooperation on Harmonization of Technical Requirements for Registration of Veterinary Medicinal Products (VICH).This paper addresses challenges and discusses some key aspects that should be considered when validating biological methods. A different statistical approach and non-parametric statistics was introduced in validation protocol in order to derive useful information from experimental data. This approach is applicable for a wide range of methods.In conclusion, the previous virus titration method had showed to be precise, accurate, linear, robust and in accordance with current regulatory standards, which indicates that there is no need for additional re-development or upgrades of the method for its suitability for intended use.