Some remarks about the analysis of active control studies

In an active-controlled trial, the experimental treatment can be declared to be non-inferior to the control if the confidence interval for the difference excludes a fixed pre-specified margin. Recently, some articles have discussed an alternative method where the data from the current study and placebo-controlled studies for the active control are combined together into a single test statistic to test whether a fixed fraction of the effect of the active control is preserved. It has been shown that, conditional on nuisance parameters from the active-controlled study, a fixed margin can be defined that will be operationally equivalent to this latter method. In this article, we will discuss statistical properties associated with these approaches. Specifically, the interim monitoring boundaries and level of evidence will be considered.     

Optimization and validation of spectrofluorimetric method for determination of cefadroxile and cefuroxime sodium in pharmaceutical formulations

A simple, accurate, precise and validated spectrofluorimetric method is proposed for the determination of two cephalosporins, namely, cefadroxile (cefa) and cefuroxime sodium (cefu) in pharmaceutical formulations. The method is based on a reaction between cephalosporins with 1,2‐naphthoquinone‐4‐sulfonate in alkaline medium, to form fluorescent derivatives that are extracted with chloroform and subsequently measured at 610 and 605 nm after excitation at 470 and 460 nm for cefa and cefu respectively. The optimum experimental conditions have been studied. Beer's law is obeyed over the concentrations of 20–70 ng/mL and 15–40 ng/mL for cefa and cefu, respectively. The detection limits were 4.46 ng/mL and 3.02 ng/mL with a linear regression correlation coefficient of 0.9984 and 0.998, and recoveries ranging 97.50–109.96% and 95.73–98.89% for cefa and cefu, respectively. The effects of pH, temperature, reaction time, 1,2‐naphthoquinone‐4‐sulfonic concentration and extraction solvent on the determination of cefa and cefu, have been examined. The proposed method can be applied for the determination of cefa and cefu in pharmaceutical formulations in quality control laboratories. Copyright © 2013 John Wiley & Sons, Ltd.     

The Use of Two‐Way Linear Mixed Models in Multitreatment Meta‐Analysis

Summary Meta‐analysis summarizes the results of a series of trials. When more than two treatments are included in the trials and when the set of treatments tested differs between trials, the combination of results across trials requires some care. Several methods have been proposed for this purpose, which feature under different labels, such as network meta‐analysis or mixed treatment comparisons. Two types of linear mixed model can be used for meta‐analysis. The one expresses the expected outcome of treatments as a contrast to a baseline treatment. The other uses a classical two‐way linear predictor with main effects for treatment and trial. In this article, we compare both types of model and explore under which conditions they give equivalent results. We illustrate practical advantages of the two‐way model using two published datasets. In particular, it is shown that between‐trial heterogeneity as well as inconsistency between different types of trial is straightforward to account for.     

Calibration of multivariate scatter plots for exploratory analysis of relations within and between sets of variables in genomic research

The scatter plot is a well known and easily applicable graphical tool to explore relationships between two quantitative variables. For the exploration of relations between multiple variables, generalisations of the scatter plot are useful. We present an overview of multivariate scatter plots focussing on the following situations. Firstly, we look at a scatter plot for portraying relations between quantitative variables within one data matrix. Secondly, we discuss a similar plot for the case of qualitative variables. Thirdly, we describe scatter plots for the relationships between two sets of variables where we focus on correlations. Finally, we treat plots of the relationships between multiple response and predictor variables, focussing on the matrix of regression coefficients. We will present both known and new results, where an important original contribution concerns a procedure for the inclusion of scales for the variables in multivariate scatter plots. We provide software for drawing such scales. We illustrate the construction and interpretation of the plots by means of examples on data collected in a genomic research program on taste in tomato.     

Optimally weighted Z-test is a powerful method for combining probabilities in meta-analysis

The inverse normal and Fisher's methods are two common approaches for combining P-values. Whitlock demonstrated that a weighted version of the inverse normal method, or 'weighted Z-test', is superior to Fisher's method for combining P-values for one-sided T-tests. The problem with Fisher's method is that it does not take advantage of weighting and loses power to the weighted Z-test when studies are differently sized. This issue was recently revisited by Chen, who observed that Lancaster's variation of Fisher's method had higher power than the weighted Z-test. Nevertheless, the weighted Z-test has comparable power to Lancaster's method when its weights are set to square roots of sample sizes. Power can be further improved when additional information is available. Although there is no single approach that is the best in every situation, the weighted Z-test enjoys certain properties that make it an appealing choice as a combination method for meta-analysis.     

The combination of two‐dimensional and three‐dimensional analysis methods contributes to the understanding of glioblastoma spatial heterogeneity

Heterogeneity is regarded as the major factor leading to the poor outcomes of glioblastoma (GBM) patients. However, conventional two‐dimensional (2D) analysis methods, such as immunohistochemistry and immunofluorescence, have limited capacity to reveal GBM spatial heterogeneity. Thus, we sought to develop an effective analysis strategy to increase the understanding of GBM spatial heterogeneity. Here, 2D and three‐dimensional (3D) analysis methods were compared for the examination of cell morphology, cell distribution and large intact structures, and both types of methods were employed to dissect GBM spatial heterogeneity. The results showed that 2D assays showed only cross‐sections of specimens but provided a full view. To visualize intact GBM specimens in 3D without sectioning, the optical tissue clearing methods CUBIC and iDISCO+ were used to clear opaque specimens so that they would become more transparent, after which the specimens were imaged with a two‐photon microscope. The 3D analysis methods showed specimens at a large spatial scale at cell‐level resolution and had overwhelming advantages in comparison to the 2D methods. Furthermore, in 3D, heterogeneity in terms of cell stemness, the microvasculature, and immune cell infiltration within GBM was comprehensively observed and analysed. Overall, we propose that 2D and 3D analysis methods should be combined to provide much greater detail to increase the understanding of GBM spatial heterogeneity.     

New spectrofluorimetric method for determination of cephalosporins in pharmaceutical formulations

A simple, accurate, precise spectrofluorimetric method has been proposed for the determination of three cephalosporins, namely, cefixime (cefi), cephalexine (ceph), and cefotaxime sodium (cefo) in pharmaceutical formulations. This method is based on a reaction between cephalosporins with 8‐hydroxy‐1,3,6‐pyrenetrisulfonic acid trisodium salt (HPTS) in alkaline medium, at pH 12.0 for cefi and 13.0 for ceph and cefo to give highly fluorescent derivatives extracted with chloroform and subsequent measurements of the formed fluorescent products at 520, 500 and 510 nm after excitation at 480, 470 and 480 nm for cefi, ceph and cefo respectively. The optimum experimental conditions have been studied. Beer's law is obeyed over concentrations of 10–60 ng/mL, 5–35 ng/mL and 10–60 ng/mL for cefi, ceph and cefo, respectively. The detection limits were 4.20 ng/mL, 2.54 ng/mL and 4.09 ng/mL for cefi, ceph and cefo, respectively, with a linear regression correlation coefficient of 0.99783, 0.99705 and 0.9978 and recoveries in ranges 96.96–105.77, 96.13–102.55 and 95.45–105.39% for cefi, ceph and cefo, respectively. This method is simple and can be applied for the determination of cefi, ceph and cefo in pharmaceutical formulations in quality control laboratories. Copyright © 2012 John Wiley & Sons, Ltd.     

A note on pseudo‐observations and left‐truncation

Pseudo‐observations have been introduced as a way to perform regression analysis of a mean value parameter related to a right‐censored time‐to‐event outcome, such as the survival probability or the restricted mean survival time. Since the introduction of the approach there have been several extensions from the original setting. However, the proper definition and performance of pseudo‐observations under left‐truncation has not yet been addressed. Here, we look at two types of pseudo‐observations under right‐censoring and left‐truncation. We explored their performance in a simulation study and applied them to data on diabetes patients with left‐truncation.     

A stage‐wise approach for the analysis of multi‐environment trials

Plant breeders and variety testing agencies routinely test candidate genotypes (crop varieties, lines, test hybrids) in multiple environments. Such multi‐environment trials can be efficiently analysed by mixed models. A single‐stage analysis models the entire observed data at the level of individual plots. This kind of analysis is usually considered as the gold standard. In practice, however, it is more convenient to use a two‐stage approach, in which experiments are first analysed per environment, yielding adjusted means per genotype, which are then summarised across environments in the second stage. Stage‐wise approaches suggested so far are approximate in that they cannot fully reproduce a single‐stage analysis, except in very simple cases, because the variance–covariance matrix of adjusted means from individual environments needs to be approximated by a diagonal matrix. This paper proposes a fully efficient stage‐wise method, which carries forward the full variance–covariance matrix of adjusted means from the individual environments to the analysis across the series of trials. Provided the variance components are known, this method can fully reproduce the results of a single‐stage analysis. Computations are made efficient by a diagonalisation of the residual variance–covariance matrix, which necessitates a corresponding linear transformation of both the first‐stage estimates (e.g. adjusted means and regression slopes for plot covariates) and the corresponding design matrices for fixed and random effects. We also exemplify the extension of the general approach to a three‐stage analysis. The method is illustrated using two datasets, one real and the other simulated. The proposed approach has close connections with meta‐analysis, where environments correspond to centres and genotypes to medical treatments. We therefore compare our theoretical results with recently published results from a meta‐analysis.     

Application of multivariate analysis and mass transfer principles for refinement of a 3‐L bioreactor scale‐down model—when shake flasks mimic 15,000‐L bioreactors better

Characterization of manufacturing processes is key to understanding the effects of process parameters on process performance and product quality. These studies are generally conducted using small‐scale model systems. Because of the importance of the results derived from these studies, the small‐scale model should be predictive of large scale. Typically, small‐scale bioreactors, which are considered superior to shake flasks in simulating large‐scale bioreactors, are used as the scale‐down models for characterizing mammalian cell culture processes. In this article, we describe a case study where a cell culture unit operation in bioreactors using one‐sided pH control and their satellites (small‐scale runs conducted using the same post‐inoculation cultures and nutrient feeds) in 3‐L bioreactors and shake flasks indicated that shake flasks mimicked the large‐scale performance better than 3‐L bioreactors. We detail here how multivariate analysis was used to make the pertinent assessment and to generate the hypothesis for refining the existing 3‐L scale‐down model. Relevant statistical techniques such as principal component analysis, partial least square, orthogonal partial least square, and discriminant analysis were used to identify the outliers and to determine the discriminatory variables responsible for performance differences at different scales. The resulting analysis, in combination with mass transfer principles, led to the hypothesis that observed similarities between 15,000‐L and shake flask runs, and differences between 15,000‐L and 3‐L runs, were due to pCO₂ and pH values. This hypothesis was confirmed by changing the aeration strategy at 3‐L scale. By reducing the initial sparge rate in 3‐L bioreactor, process performance and product quality data moved closer to that of large scale. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1370–1380, 2015     

Evaluation of association of maternal IL‐10 polymorphisms with risk of preeclampsia by A meta‐analysis

Emerging evidence shows that interleukin (IL)‐10 gene polymorphisms can regulate its expression level and thus influence person's susceptibility to preeclampsia. However, various published results were inconsistent. To explore the association between maternal IL‐10 gene polymorphisms and preeclampsia, we performed a meta‐analysis based upon 11 individual studies here. Our meta‐analysis results indicated that IL‐10 ‐819C/T (C versus T, OR = 1.28, 95% CI = 1.08–1.50, P = 0.003) and ‐592C/A (C versus A, OR = 1.28, 95% CI = 1.03–1.59, P = 0.03) polymorphisms were associated with preeclampsia. Although there was no overall association between ‐1082A/G polymorphism and preeclampsia (G versus A, OR = 0.93, 95% CI = 0.77–1.13, P = 0.49), such association existed among Asian (G versus A, OR = 1.29, 95% CI = 1.04–1.60, P = 0.02) and South American (G versus A, OR = 0.72, 95% CI = 0.54–0.94, P = 0.02) populations in the subgroup analysis stratified by continents.     

Reduced rank hazard regression with fixed and time‐varying effects of the covariates

Modelling survival data from long‐term follow‐up studies presents challenges. The commonly used proportional hazards model should be extended to account for dynamic behaviour of the effects of fixed covariates. This work illustrates the use of reduced rank models in survival data, where some of the covariate effects are allowed to behave dynamically in time and some as fixed. Time‐varying effects of the covariates can be fitted by using interactions of the fixed covariates with flexible transformations of time based on b‐splines. To avoid overfitting, a reduced rank model will restrict the number of parameters, resulting in a more sensible fit to the data. This work presents the basic theory and the algorithm to fit such models. An application to breast cancer data is used for illustration of the suggested methods.     

A versatile chiral selector for determination of enantiomeric composition of fluorescent and nonfluorescent chiral molecules using steady-state fluorescence spectroscopy

A fluorescent chiral molecular micelle (FCMM), poly (sodium N-undecanoyl-L-phenylalaninate) (poly-L-SUF), was developed as a chiral selector for enantiomeric recognition and determination of enantiomeric composition of four fluorescent and four nonfluorescent chiral molecules by use of steady-state fluorescence spectroscopy. The influence of FCMM concentration, buffer pH and complexation medium on FCMM-analyte host-guest complexation, and the emission spectral properties of the resulting complexes were investigated. The chiral interactions of the analytes,1,1'-binaphthyl-2,2'-diamine, 1-(9-anthryl)-2,2,2-trifluoroethanol, propranolol, naproxen, chloromethyl menthyl ether (CME), citramalic acid, tartaric acid, and limonene (LIM), in the presence of poly-L-SUF were based on diastereomeric complex formation. The figures of merit obtained from the partial-least-squares regression modeling of the calibration samples suggested good prediction ability for the validation of six of the eight chiral analytes. Better host-guest complexation of the more hydrophobic molecules, CME and LIM, were obtained in methanol/water mixtures, resulting in better predictability of the regression models. Prediction ability of the models was evaluated by use of the root-mean-square percent relative error (RMS%RE) and was found to range from 1.77 to 15.80% (buffer), 1.26 to 7.95% (25:75 methanol/water), and 1.21 to 4.28% (75:25 methanol/water).     

Isolation of Components from the Low-Sulphur Proteins of Wool by Fractional Precipitation

The two major components of the low-sulphur S-carboxymethylkerateine fraction from wool (components 7 and 8) have been isolated by methods involving fractional precipitation from n-propanol/water and from 4 M LiBr. The materials obtained in this way are similar in amino acid composition and in gel electrophoresis properties to fractions obtained by column chromatographic techniques and are of at least equal purity. The procedures are relatively quick and can be scaled up.     

Analysis of macamides in samples of Maca (Lepidium meyenii) by HPLC-UV-MS/MS

The macamides are a distinct class of secondary metabolites that have so far been found only in Lepidium meyenii Walp. (Maca). Using HPLC-UV-MS/MS, the main macamides have been identified as n-benzylhexadecanamide, n-benzyl-(9Z)-octadecenamide, n-benzyl-(9Z, 12Z)-octadecadienamide, n-benzyl-(9Z, 12Z, 15Z)-octadecatrienamide and n-benzyloctadecanamide. The identities of n-benzyl-(9Z)-octadecenamide and n-benzyl-(9Z, 12Z)-octadecadienamide were confirmed by comparison of chromatographic and spectral properties with synthetic analogues. Total macamides have been quantified by HPLC-UV in plant material from different vendors using n-benzylhexadecanamide as an external standard. The amount of macamides in the dried plant material ranged from 0.0016 to 0.0123%.     

Molecular determinants of the ATP hydrolysis asymmetry of the CCT chaperonin complex

The eukaryotic cytosolic chaperonin CCT is a molecular machine involved in assisting the folding of proteins involved in important cellular processes. Like other chaperonins, CCT is formed by a double‐ring structure but, unlike all of them, each ring is composed of eight different, albeit homologous subunits. This complexity has probably to do with the specificity in substrate interaction and with the mechanism of protein folding that takes place during the chaperonin functional cycle, but its detailed molecular basis remains unknown. We have analyzed the known proteomes in search of residues that are differentially conserved in the eight subunits, as predictors of functional specificity (specificity‐determining positions; SDPs). We have found that most of these SDPs are located near the ATP binding site, and that they define four CCT clusters, corresponding to subunits CCT3, CCT6, CCT8 and CCT1/2/4/5/7. Our results point to a spatial organisation of the CCT subunits in two opposite areas of the ring and provide a molecular explanation for the previously described asymmetry in the hydrolysis of ATP. Proteins 2014; 82:703–707. © 2014 Wiley Periodicals, Inc.