Design and analysis of bridging studies with prior probabilities on the null and alternative hypotheses

The pharmaceutical industry and regulatory agencies are increasingly interested in conducting bridging studies in order to bring an approved drug product from the original region (eg, United States or European Union) to a new region (eg, Asian-Pacific countries). In this article, we provide a new methodology for the design and analysis of bridging studies by assuming prior knowledge on how the null and alternative hypotheses in the original, foreign study are related to the null and alternative hypotheses in the bridging study and setting the type I error for the bridging study according to the strength of the foreign-study evidence. The new methodology accounts for randomness in the foreign-study evidence and controls the average type I error of the bridging study over all possibilities of the foreign-study evidence. In addition, the new methodology increases statistical power, when compared to approaches that do not use foreign-study evidence, and it allows for the possibility of not conducting the bridging study when the foreign-study evidence is unfavorable. Finally, we conducted extensive simulation studies to demonstrate the usefulness of the proposed methodology.     

A strategy for finding regions of similarity in complete genome sequences

MOTIVATION: Complete genomic sequences will become available in the future. New methods to deal with very large sequences (sizes beyond 100 kb) efficiently are required. One of the main aims of such work is to increase our understanding of genome organization and evolution. This requires studies of the locations of regions of similarity. RESULTS: We present here a new tool, ASSIRC ('Accelerated Search for SImilarity Regions in Chromosomes'), for finding regions of similarity in genomic sequences. The method involves three steps: (i) identification of short exact chains of fixed size, called 'seeds', common to both sequences, using hashing functions; (ii) extension of these seeds into putative regions of similarity by a 'random walk' procedure; (iii) final selection of regions of similarity by assessing alignments of the putative sequences. We used simulations to estimate the proportion of regions of similarity not detected for particular region sizes, base identity proportions and seed sizes. This approach can be tailored to the user's specifications. We looked for regions of similarity between two yeast chromosomes (V and IX). The efficiency of the approach was compared to those of conventional programs BLAST and FASTA, by assessing CPU time required and the regions of similarity found for the same data set. AVAILABILITY: Source programs are freely available at the following address: ftp://ftp.biologie.ens. fr/pub/molbio/assirc.tar.gz CONTACT: vincens@biologie.ens.fr, hazout@urbb.jussieu.fr      

Flanking Regulatory Sequences of the Tetrahymena R Deletion Element Determine the Boundaries of DNA Rearrangement

In the ciliate Tetrahymena thermophila, thousands of DNA segments of variable size are eliminated from the developing somatic macronucleus by specific DNA rearrangements. It is unclear whether rearrangement of the many different DNA elements occurs via a single mechanism or via multiple rearrangement systems. In this study, we characterized in vivo cis-acting sequences required for the rearrangement of the 1.1-kbp R deletion element. We found that rearrangement requires specific sequences flanking each side of the deletion element. The required sequences on the left side appear to span roughly a 70-bp region that is located at least 30 bp from the rearrangement boundary. When we moved the location of the left cis-acting sequences closer to the eliminated region, we observed a rightward shift of the rearrangement boundary such that the newly formed deletion junction retained its original distance from this flanking region. Likewise, when we moved the flanking region as much as 500 bp away from the deletion element, the rearrangement boundary shifted to remain in relative juxtaposition. Clusters of base substitutions made throughout this critical flanking region did not affect rearrangement efficiency or accuracy, which suggests a complex nature for this regulatory sequence. We also found that the right flanking region effectively replaced the essential sequences identified on the left side, and thus, the two flanking regions contain sequences of analogous function despite the lack of obvious sequence identity. These data taken together indicate that the R-element flanking regions contain sequences that position the rearrangement boundaries from a short distance away. Previously, a 10-bp polypurine tract flanking the M-deletion element was demonstrated to act from a distance to determine its rearrangement boundaries. No apparent sequence similarity exists between the M and R elements. The functional similarity between these different cis-acting sequences of the two elements is firm support for a common mechanism controlling Tetrahymena rearrangement.     

合并与不合并：两个相似性聚类分析方法比较

以山西省4638种昆虫在7个地理小区的分布、内蒙古7766种昆虫在14个地理小区的分布和中国16804属昆虫在67个生态区域的分布3组数据为样本,用传统的层层合并的相似性聚类分析法(SCA)和新的不需合并的多元相似性聚类分析法(MSCA)进行运算分析,对比结果表明,不合并法都能得到既符合统计学逻辑,又符合地理学、生物学逻辑的结果;合并法在参与小区较少时,还能够得到与不合并法类似的结果,随着参与小区的增多,聚类结构发生变化,以致聚类功能彻底丧失.无论两种聚类结果差异大小,其性质都迥然不同:不合并法的相似性系数是固有的、互相独立的、同时存在的,聚类结果是所有小区之间关系亲疏、距离远近的状态;合并法的每个相似性系数都是合并的依据或结果,前一个系数是后一个系数产生的条件,后一个系数是前一个系数消亡的结果,严格按照顺序,当最后一个系数产生时,前面所有系数和所有小区都已不复存在,聚类结果只是记录不断合并、不断消亡的过程.因此在肯定合并法历史价值的同时,认为申效诚等创建的多元相似性系数公式及多元相似性聚类分析法摈弃合并降阶这一产生偏差和错误的根源,能够得出相对客观的聚类结果,是生物地理学研究领域有效的聚类分析工具,必将推动生物地理学定量研究迈入一个新阶段.     

Bayesian sample size determination using commensurate priors to leverage preexperimental data

This paper develops Bayesian sample size formulae for experiments comparing two groups, where relevant preexperimental information from multiple sources can be incorporated in a robust prior to support both the design and analysis. We use commensurate predictive priors for borrowing of information and further place Gamma mixture priors on the precisions to account for preliminary belief about the pairwise (in)commensurability between parameters that underpin the historical and new experiments. Averaged over the probability space of the new experimental data, appropriate sample sizes are found according to criteria that control certain aspects of the posterior distribution, such as the coverage probability or length of a defined density region. Our Bayesian methodology can be applied to circumstances that compare two normal means, proportions, or event times. When nuisance parameters (such as variance) in the new experiment are unknown, a prior distribution can further be specified based on preexperimental data. Exact solutions are available based on most of the criteria considered for Bayesian sample size determination, while a search procedure is described in cases for which there are no closed-form expressions. We illustrate the application of our sample size formulae in the design of clinical trials, where pretrial information is available to be leveraged. Hypothetical data examples, motivated by a rare-disease trial with an elicited expert prior opinion, and a comprehensive performance evaluation of the proposed methodology are presented.     

ISOLATION OF ccmKLMN GENES FROM THE MARINE CYANOBACTERIUM, SYNECHOCOCCUS SP. PCC7002 (CYANOPHYCEAE), AND EVIDENCE THAT CcmM IS ESSENTIAL FOR CARBOXYSOME ASSEMBLY

A high CO₂ requiring mutant of the marine cyanobacterium Synechococcus PCC7002 was generated using a random gene-tagging procedure. This mutant demonstrated a reduced photosynthetic affinity for inorganic carbon (C_i) and accumulated high internal levels of C_i that could not be used for photosynthesis. Analysis of the mutant genomic DNA showed that the mutagenesis had disrupted a cluster of genes involved in the cyanobacterial CO₂ concentrating mechanism (CCM), the so-called ccm genes. These characteristics are consistent with a cyanobacterial mutant with defects in carboxysome assembly and/or functioning. Further genomic analyses indicated that the genes of the Synechococcus PCC7002 operon, ccmKLMN , are structurally similar to those of two closely related cyanobacteria, Synechococcus PCC7942 and Synechocystis PCC6803. The Synechococcus PCC7002 ccmM gene, which encodes a polypeptide with a predicted size of 70 kDa, was the direct target of the mutagenesis event. The CcmM protein has two distinct regions: an N-terminal region that shows similarity to an archaeon gamma carbonic anhydrase and a C-terminal region that contains repeated domains demonstrating sequence similarity to the small subunit of Rubisco. Physiological analysis of a ccmM -defined mutant showed that these cells were essentially identical to the original mutant; they required high CO₂ concentrations for growth, they had a low photosynthetic affinity for C_i, and they internalized C_i to high levels. Moreover, ultrastructural examination showed that both the original and the defined mutants lack carboxysomes. Thus, our results demonstrate that the ccmM gene of Synechococcus PCC7002 encodes a polypeptide that is essential for carboxysome assembly and therefore for proper functioning of the cyanobacterial CCM.     

Improving data interpretation of fragmentary data-sets on invertebrate dispersal with permutation tests

Biological data often tend to have heterogeneous, discontinuous non-normal distributions. Statistical non-parametric tests, like the Mann–Whitney U-test or the extension for more than two samples, the Kruskal–Wallis test, are often used in these cases, although they assume certain preconditions which are often ignored. We developed a permutation test procedure that uses the ratio of the interquartile distances and the median differences of the original non-classified data to assess the properties of the real distribution more appropriately than the classical methods. We used this test on a heterogeneous, skewed biological data set on invertebrate dispersal and showed how different the reactions of the Kruskal–Wallis test and the permutation approach are. We then evaluated the new testing procedure with reproducible data that were generated from the normal distribution. Here, we tested the influence of four different experimental trials on the new testing procedure in comparison to the Kruskal–Wallis test. These trials showed the impact of data that were varying in terms of (a) negative correlation between variances and means of the samples, (b) changing variances that were not correlated with the means of the samples, (c) constant variances and means, but different sample sizes and in trials (d) we evaluated the testing power of the new procedure. Due to the different test statistics, the permutation test reacted more sensibly to the data presented in trials (a) and c) and non-uniformly in trial (b). In the evaluation of the testing power, no significant differences between the Kruskal–Wallis test and the new permutation testing procedure could be detected. We consider this test to be an alternative for working on heterogeneous data where the preconditions of the classical non-parametric tests are not met.     

How much confidence do we need in animal experiments? Statistical assumptions in sample size estimation

Statistical sample size calculation is a crucial part of planning nonhuman animal experiments in basic medical research. The 3R principle intends to reduce the number of animals to a sufficient minimum. When planning experiments, one may consider the impact of less rigorous assumptions during sample size determination as it might result in a considerable reduction in the number of required animals. Sample size calculations conducted for 111 biometrical reports were repeated. The original effect size assumptions remained unchanged, but the basic properties (type 1 error 5%, two-sided hypothesis, 80% power) were varied. The analyses showed that a less rigorous assumption on the type 1 error level (one-sided 5% instead of two-sided 5%) was associated with a savings potential of 14% regarding the original number of required animals. Animal experiments are predominantly exploratory studies. In light of the demonstrated potential reduction in the numbers of required animals, researchers should discuss whether less rigorous assumptions during the process of sample size calculation may be reasonable for the purpose of optimizing the number of animals in experiments according to the 3R principle.     

Les essais cliniques en médecine nucléaire

The EU clinical trials directive (2001/20/EC) was published on the 4th April 2001 and was transposed into French law in 2004. This new clinical trial regulation has modified considerably the research area including clinical trials conducted with radiopharmaceutical medicinal products. This new regulation aims at ensuring the protection of the health and safety of clinical trial participants, the ethical soundness and the reliability and robustness of data generated in clinical trials. In practice, the sponsor has to submit a clinical trial application to the Afssaps for authorization and to the concerned Ethics Committee for a positive opinion. The content of the clinical trial application regarding the investigational medicinal product is very detailed and a heavy technical dossier could be required in order to justify the quality of the medicinal product used in the clinical trial. Furthermore, pharmacy and radiopharmacy required specific authorizations for preparing these medicinal products. This new regulation could refrain nuclear medicine from conducting clinical trials.     

The effect of SNP discovery method and sample size on estimation of population genetic data for Chinese and Indian rhesus macaques (<Emphasis Type="Italic">Macaca mulatta</Emphasis>)

This study was designed to address issues regarding sample size and marker location that have arisen from the discovery of SNPs in the genomes of poorly characterized primate species and the application of these markers to the study of primate population genetics. We predict the effect of discovery sample size on the probability of discovering both rare and common SNPs and then compare this prediction with the proportion of common and rare SNPs discovered when different numbers of individuals are sequenced. Second, we examine the effect of genomic region on estimates of common population genetic data, comparing markers from both coding and non-coding regions of the rhesus macaque genome and the population genetic data calculated from these markers, to measure the degree and direction of bias introduced by SNPs located in coding versus non-coding regions of the genome. We found that both discovery sample size and genomic region surveyed affect SNP marker attributes and population genetic estimates, even when these are calculated from an expanded data set containing more individuals than the original discovery data set. Although none of the SNP detection methods or genomic regions tested in this study was completely uninformative, these results show that each has a different kind of genetic variation that is suitable for different purposes, and each introduces specific types of bias. Given that each SNP marker has an individual evolutionary history, we calculated that the most complete and unbiased representation of the genetic diversity present in the individual can be obtained by incorporating at least 10 individuals into the discovery sample set, to ensure the discovery of both common and rare polymorphisms.     

Sample size recalculation in multicenter randomized controlled clinical trials based on noncomparative data

Many late-phase clinical trials recruit subjects at multiple study sites. This introduces a hierarchical structure into the data that can result in a power-loss compared to a more homogeneous single-center trial. Building on a recently proposed approach to sample size determination, we suggest a sample size recalculation procedure for multicenter trials with continuous endpoints. The procedure estimates nuisance parameters at interim from noncomparative data and recalculates the sample size required based on these estimates. In contrast to other sample size calculation methods for multicenter trials, our approach assumes a mixed effects model and does not rely on balanced data within centers. It is therefore advantageous, especially for sample size recalculation at interim. We illustrate the proposed methodology by a study evaluating a diabetes management system. Monte Carlo simulations are carried out to evaluate operation characteristics of the sample size recalculation procedure using comparative as well as noncomparative data, assessing their dependence on parameters such as between-center heterogeneity, residual variance of observations, treatment effect size and number of centers. We compare two different estimators for between-center heterogeneity, an unadjusted and a bias-adjusted estimator, both based on quadratic forms. The type 1 error probability as well as statistical power are close to their nominal levels for all parameter combinations considered in our simulation study for the proposed unadjusted estimator, whereas the adjusted estimator exhibits some type 1 error rate inflation. Overall, the sample size recalculation procedure can be recommended to mitigate risks arising from misspecified nuisance parameters at the planning stage.     

A new index of interactivity in parasite communities.

A new index of interactivity which allows objective evaluation and comparison of interactivity in communities between different host species is presented. The index is derived from the equations for species-accumulation curves generated using non-linear regression (with the Levenberg-Marquardt algorithm) of sample infracommunity richness data. It is advantageous in that it requires only presence/absence data to calculate, is applicable to all parasite taxa (including asexual species), is largely independent of sample size and allows objective comparison of parasite communities while correcting for differences in total richness. Iterative randomisation of infracommunity richness values to generate a mean value for the index avoids spurious results which may be generated by heterogeneity in infracommunity richness and the variation this produces in the non-linear regression results.     

Bryophytic similarity of the Italian regions with a focus on the Ligurian region

The bryophyte flora of Liguria region is compared with data available for other Italian regions. Comparisons were made in terms of biogeographical coherence, floristic similarity, and the number of scientific studies for each region. The aim was to provide a provisional evaluation based on bibliographic data, but with useful insights for an objective assessment of the state of knowledge and for the continuation of the study of hornworts, liverworts, and mosses in the Liguria.     

Sample size requirements for studies of treatment effects on beta-cell function in newly diagnosed type 1 diabetes

Preservation of β-cell function as measured by stimulated C-peptide has recently been accepted as a therapeutic target for subjects with newly diagnosed type 1 diabetes. In recently completed studies conducted by the Type 1 Diabetes Trial Network (TrialNet), repeated 2-hour Mixed Meal Tolerance Tests (MMTT) were obtained for up to 24 months from 156 subjects with up to 3 months duration of type 1 diabetes at the time of study enrollment. These data provide the information needed to more accurately determine the sample size needed for future studies of the effects of new agents on the 2-hour area under the curve (AUC) of the C-peptide values. The natural log(x), log(x+1) and square-root (√x) transformations of the AUC were assessed. In general, a transformation of the data is needed to better satisfy the normality assumptions for commonly used statistical tests. Statistical analysis of the raw and transformed data are provided to estimate the mean levels over time and the residual variation in untreated subjects that allow sample size calculations for future studies at either 12 or 24 months of follow-up and among children 8-12 years of age, adolescents (13-17 years) and adults (18+ years). The sample size needed to detect a given relative (percentage) difference with treatment versus control is greater at 24 months than at 12 months of follow-up, and differs among age categories. Owing to greater residual variation among those 13-17 years of age, a larger sample size is required for this age group. Methods are also described for assessment of sample size for mixtures of subjects among the age categories. Statistical expressions are presented for the presentation of analyses of log(x+1) and √x transformed values in terms of the original units of measurement (pmol/ml). Analyses using different transformations are described for the TrialNet study of masked anti-CD20 (rituximab) versus masked placebo. These results provide the information needed to accurately evaluate the sample size for studies of new agents to preserve C-peptide levels in newly diagnosed type 1 diabetes.     

Combinatorial mutagenesis and pseudorevertant analysis to characterize regions in loop E of the CP47 protein in Synechocystis sp. PCC 6803.

Deletion of the I265-F268 and T271-K277 regions in the large lumenally exposed loop of the CP47 protein are known to lead to a loss of photoautotrophic growth. Here, these regions have been investigated by combinatorial mutagenesis and pseudorevertant mapping. No single amino-acid residue in the I265-F268 region was found to be critical for function, but a large hydrophobic residue at position 267 and preferentially an aromatic residue at position 268 appeared to be required for photoautotrophic growth. Starting from an obligate photoheterotrophic mutant lacking the T271-K277 region, photoautotrophic pseudorevertants were generated with short in-frame tandem repeats near the site of the original deletion, partially or fully restoring the length of the original protein. These pseudorevertants were sensitive to oxygen indicating that the T271-K277 region may provide PS II stability and/or protection against oxygen-dependent photoinactivation. Pseudorevertants with much improved photoautotrophic growth were also generated for one of the combinatorial mutants in the I265-F268 region. Surprisingly, the secondary mutations in these pseudorevertants mapped to the ferrochelatase gene. We speculate that the secondary mutation in ferrochelatase gene resulted in altered ferrochelatase activity. Decreased heme (phycobilin) biosynthesis and/or increased chlorophyll biosynthesis could then lead to improved PS II performance of the combinatorial CP47 mutant.     

Effective Modification of Particle Surface Properties Using Ultrasonic Water Mist

The goal of the present study was to design a new technique to modify particle surface properties and, through that, to improve flowability of poorly flowing drug thiamine hydrochloride and pharmaceutical sugar lactose monohydrate of two different grades. The powdered particles were supplied by a vibratory feeder and exposed to an instantaneous effect of water mist generated from an ultrasound nebulizer. The processed and original powders were evaluated with respect to morphology (scanning electron microscopy, atomic force microscopy, and spatial filtering technique), flow, and solid state properties. It was found that rapid exposition of pharmaceutical materials by water mist resulted in the improvement of powder technical properties. The evident changes in flowability of coarser lactose were obviously due to smoothing of particle surface and decreasing in the level of fines with very slight increment in particle size. The changes in thiamine powder flow were mainly due to narrowing in particle size distribution where the tendency for better flow of finer lactose was related to surface and size modifications. The aqueous mist application did not cause any alteration of the crystal structures of the studied materials. The proposed water mist treatment technique appears to be a robust, rapid, and promising tool for the improvement of the technological properties of pharmaceutical powders.     

Identification of new HLA class I region genes by sample sequencing

 Although many human major histocompatibility genes have been identified, relatively few have been localized to the class I region. We searched for new class I region genes by sample sequencing, a process in which short stretches of random genomic sequence are generated from cosmids and then compared with sequences deposited in nucleotide databases. Four class I region cosmids were isolated for sample sequencing by screening a chromosome 6 specific cosmid library with probes derived from specific class I region genes or with overlapping class I region yeast artificial chromosomes. Cosmids were sonnicated to produce fragments of 0.5 – 1 kilobases, subcloned, and sequenced using an automated sequencer. Sequences were then compared with nucleotide sequences deposited in the GenBank databases using the BLASTN algorithm. A number of potential new class I region genes were identified, including a cDNA with similarity to the tre oncogene, the trans-activating factor SC1 (TCF19), and a member of the interferon inducible 1 – 8 gene family. These observations suggest that sample sequencing is an efficient method for identifying new class I region genes, which can be applied to other regions of the genome and to other species, and support previous observations that the class I region contains a variety of genes other than those encoding HLA antigens. Received: 10 December 1996 / Revised: 7 January 1997     

Biosimilars: Key regulatory considerations and similarity assessment tools

A biosimilar drug is defined in the US Food and Drug Administration (FDA) guidance document as a biopharmaceutical that is highly similar to an already licensed biologic product (referred to as the reference product) notwithstanding minor differences in clinically inactive components and for which there are no clinically meaningful differences in purity, potency, and safety between the two products. The development of biosimilars is a challenging, multistep process. Typically, the assessment of similarity involves comprehensive structural and functional characterization throughout the development of the biosimilar in an iterative manner and, if required by the local regulatory authority, an in vivo nonclinical evaluation, all conducted with direct comparison to the reference product. In addition, comparative clinical pharmacology studies are conducted with the reference product. The approval of biosimilars is highly regulated although varied across the globe in terms of nomenclature and the precise criteria for demonstrating similarity. Despite varied regulatory requirements, differences between the proposed biosimilar and the reference product must be supported by strong scientific evidence that these differences are not clinically meaningful. This review discusses the challenges faced by pharmaceutical companies in the development of biosimilars.