Equivalence analyses of dissolution profiles with the Mahalanobis distance

For some postapproval changes, the manufacturer has to demonstrate that the dissolution profile of the drug product before the change is statistically equivalent to the dissolution profile after the change. Guidelines suggest the so‐called similarity factor f₂ as standard approach for the equivalence analysis. f₂ is a statistically questionable transformation of the Euclidean distance between both profile means and does not allow a control of the type I error rate. An alternative multivariate distance measure for quantifying the dissimilarity between both profile groups is the Mahalanobis distance. Current equivalence procedures based on the Mahalanobis distance implicate some practical problems in the dissolution context: either one chooses an exact method but the determination of a product independent equivalence margin will not be practically feasible or one chooses an approximate alternative that suffers from the bias of the Mahalanobis distance point estimate. This paper suggests the T2EQ approach for dissolution profile comparisons. T2EQ is a practically feasible equivalence procedure based on the Mahalanobis distance with an internal equivalence margin for comparing dissolution profiles. The equivalence margin is compliant with current dissolution guidelines. The operating characteristics (size, robustness, and power) are investigated via simulation: T2EQ meets the needs of both authorities and industry: not affected by the bias of the point estimate the type I error rate can be reliably controlled for various distribution assumptions and the power of T2EQ exceeds the power of methods recently discussed in the literature. These results were presented for the first time at CEN‐ISBS 2017.     

The importance of retaining a phylogenetic perspective in traits‐based community analyses

相似文献   

A comparison of individual‐based genetic distance metrics for landscape genetics

A major aim of landscape genetics is to understand how landscapes resist gene flow and thereby influence population genetic structure. An empirical understanding of this process provides a wealth of information that can be used to guide conservation and management of species in fragmented landscapes and also to predict how landscape change may affect population viability. Statistical approaches to infer the true model among competing alternatives are based on the strength of the relationship between pairwise genetic distances and landscape distances among sampled individuals in a population. A variety of methods have been devised to quantify individual genetic distances, but no study has yet compared their relative performance when used for model selection in landscape genetics. In this study, we used population genetic simulations to assess the accuracy of 16 individual‐based genetic distance metrics under varying sample sizes and degree of population genetic structure. We found most metrics performed well when sample size and genetic structure was high. However, it was much more challenging to infer the true model when sample size and genetic structure was low. Under these conditions, we found genetic distance metrics based on principal components analysis were the most accurate (although several other metrics performed similarly), but only when they were derived from multiple principal components axes (the optimal number varied depending on the degree of population genetic structure). Our results provide guidance for which genetic distance metrics maximize model selection accuracy and thereby better inform conservation and management decisions based upon landscape genetic analysis.     

Direct prediction of profiles of sequences compatible with a protein structure by neural networks with fragment‐based local and energy‐based nonlocal profiles

Locating sequences compatible with a protein structural fold is the well‐known inverse protein‐folding problem. While significant progress has been made, the success rate of protein design remains low. As a result, a library of designed sequences or profile of sequences is currently employed for guiding experimental screening or directed evolution. Sequence profiles can be computationally predicted by iterative mutations of a random sequence to produce energy‐optimized sequences, or by combining sequences of structurally similar fragments in a template library. The latter approach is computationally more efficient but yields less accurate profiles than the former because of lacking tertiary structural information. Here we present a method called SPIN that predicts Sequence Profiles by Integrated Neural network based on fragment‐derived sequence profiles and structure‐derived energy profiles. SPIN improves over the fragment‐derived profile by 6.7% (from 23.6 to 30.3%) in sequence identity between predicted and wild‐type sequences. The method also reduces the number of residues in low complex regions by 15.7% and has a significantly better balance of hydrophilic and hydrophobic residues at protein surface. The accuracy of sequence profiles obtained is comparable to those generated from the protein design program RosettaDesign 3.5. This highly efficient method for predicting sequence profiles from structures will be useful as a single‐body scoring term for improving scoring functions used in protein design and fold recognition. It also complements protein design programs in guiding experimental design of the sequence library for screening and directed evolution of designed sequences. The SPIN server is available at http://sparks‐lab.org . Proteins 2014; 82:2565–2573. © 2014 Wiley Periodicals, Inc.     

Stoichiometry of a regulatory splicing complex revealed by single‐molecule analyses

Splicing is regulated by complex interactions of numerous RNA‐binding proteins. The molecular mechanisms involved remain elusive, in large part because of ignorance regarding the numbers of proteins in regulatory complexes. Polypyrimidine tract‐binding protein (PTB), which regulates tissue‐specific splicing, represses exon 3 of α‐tropomyosin through distant pyrimidine‐rich tracts in the flanking introns. Current models for repression involve either PTB‐mediated looping or the propagation of complexes between tracts. To test these models, we used single‐molecule approaches to count the number of bound PTB molecules both by counting the number of bleaching steps of GFP molecules linked to PTB within complexes and by analysing their total emissions. Both approaches showed that five or six PTB molecules assemble. Given the domain structures, this suggests that the molecules occupy primarily multiple overlapping potential sites in the polypyrimidine tracts, excluding propagation models. As an alternative to direct looping, we propose that repression involves a multistep process in which PTB binding forms small local loops, creating a platform for recruitment of other proteins that bring these loops into close proximity.     

Detecting frogs as prey in the diets of introduced mammals: a comparison between morphological and DNA‐based diet analyses

Amphibians are currently the most threatened group of vertebrates worldwide, and introduced fauna play a major role in their decline. The control of introduced predators to protect endangered species is often based on predation rates derived from diet studies of predators, but prey detection probabilities using different techniques are variable. We measured the detectability of frogs as prey, using morphological and DNA‐based diet analyses, in the stomachs and faeces of four mammal species that have been introduced to many areas of the world. Frogs (Litoria raniformis) were fed to rats (Rattus norvegicus and R. rattus), mice (Mus musculus) and hedgehogs (Erinaceus europaeus). DNA‐based analysis outperformed morphological analysis, increasing the prey detection rate from 2% to 70% in stomachs and from 0% to 53% in faeces. In most cases, utilizing either stomachs or faeces did not affect the success of prey DNA detection; however, using faeces extended the detectability half‐life from 7 to 21 h. This study is the first to measure prey DNA detection periods in mammalian stomachs, and the first to compare prey DNA detection periods in the stomachs and faeces of vertebrates. The results indicate that DNA‐based diet analysis provides a more reliable approach for detecting amphibians as prey and has the potential to be used to estimate the rate of predation by introduced mammals on endangered amphibians.     

Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE

Background:  

In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease. Among numerous existing methods for gene selection, support vector machine-based recursive feature elimination (SVM-RFE) has become one of the leading methods and is being widely used. The SVM-based approach performs gene selection using the weight vector of the hyperplane constructed by the samples on the margin. However, the performance can be easily affected by noise and outliers, when it is applied to noisy, small sample size microarray data.     

Genome editing with the CRISPR‐Cas system: an art,ethics and global regulatory perspective

Over the last three decades, the development of new genome editing techniques, such as ODM, TALENs, ZFNs and the CRISPR‐Cas system, has led to significant progress in the field of plant and animal breeding. The CRISPR‐Cas system is the most versatile genome editing tool discovered in the history of molecular biology because it can be used to alter diverse genomes (e.g. genomes from both plants and animals) including human genomes with unprecedented ease, accuracy and high efficiency. The recent development and scope of CRISPR‐Cas system have raised new regulatory challenges around the world due to moral, ethical, safety and technical concerns associated with its applications in pre‐clinical and clinical research, biomedicine and agriculture. Here, we review the art, applications and potential risks of CRISPR‐Cas system in genome editing. We also highlight the patent and ethical issues of this technology along with regulatory frameworks established by various nations to regulate CRISPR‐Cas‐modified organisms/products.     

Complexity is costly: a meta‐analysis of parametric and non‐parametric methods for short‐term population forecasting

Short‐term forecasts based on time series of counts or survey data are widely used in population biology to provide advice concerning the management, harvest and conservation of natural populations. A common approach to produce these forecasts uses time‐series models, of different types, fit to time series of counts. Similar time‐series models are used in many other disciplines, however relative to the data available in these other disciplines, population data are often unusually short and noisy and models that perform well for data from other disciplines may not be appropriate for population data. In order to study the performance of time‐series forecasting models for natural animal population data, we assembled 2379 time series of vertebrate population indices from actual surveys. Our data were comprised of three vastly different types: highly variable (marine fish productivity), strongly cyclic (adult salmon counts), and small variance but long‐memory (bird and mammal counts). We tested the predictive performance of 49 different forecasting models grouped into three broad classes: autoregressive time‐series models, non‐linear regression‐type models and non‐parametric time‐series models. Low‐dimensional parametric autoregressive models gave the most accurate forecasts across a wide range of taxa; the most accurate model was one that simply treated the most recent observation as the forecast. More complex parametric and non‐parametric models performed worse, except when applied to highly cyclic species. Across taxa, certain life history characteristics were correlated with lower forecast error; specifically, we found that better forecasts were correlated with attributes of slow growing species: large maximum age and size for fishes and high trophic level for birds. Synthesis Evaluating the data support for multiple plausible models has been an integral focus of many ecological analyses. However, the most commonly used tools to quantify support have weighted models’ hindcasting and forecasting abilities. For many applications, predicting the past may be of little interest. Concentrating only on the future predictive performance of time series models, we performed a forecasting competition among many different kinds of statistical models, applying each to many different kinds of vertebrate time series of population abundance. Low‐dimensional (simple) models performed well overall, but more complex models did slightly better when applied to time series of cyclic species (e.g. salmon).     

Colonization of the Galápagos Islands by plants with no specific syndromes for long‐distance dispersal: a new perspective

Since nobody has witnessed the arrival of early plant colonists on isolated islands, the actual long‐distance dispersal (hereafter LDD) has historically been a matter of speculation. In the present study, we offer a new approach that evaluates whether particular syndromes for LDD (i.e. the set of traits related to diaspore dispersal by animals, wind and sea currents) have been favourable in the natural colonization of the Galápagos Islands by plants. Dispersal syndromes of the 251 native genera (509 angiosperm species) presently acknowledged as native were carefully studied, combining data from floristic lists of the Galápagos Islands, diaspore traits, characteristics of continental relatives and our own observations. We used these genera (and occasionally infrageneric groups) as the working units to infer the number of introductions and colonists. A final number of native plants was inferred and analysed after correcting by pollen records of six species from six genera previously considered exotic (palaeobotanical correction). The number of early colonists was also corrected by incorporating information from the few (n= 12) phylogenetic studies of genera from both the Galápagos Islands and the Americas (phylogenetic correction). A total of 372 colonization events were inferred for the native flora using the latest check‐list. The proportions of native colonists grouped into five categories were: endozoochory 16.4%, epizoochory 15.7%, hydrochory 18.6%, anemochory 13.3%, and unassisted diaspores 36.0%. These figures did not vary significantly on analysing only the 99 genera that include endemic species in order to rule out any human‐mediated introductions. Irrespective of the roles of the different agents involved in LDD, diaspores with no special syndrome for LDD (unassisted diapores), such as many dry fruits, have been successful in reaching and colonizing the Galápagos archipelago. This finding leads us to suggest that unpredictable and so far unknown LDD mechanisms should be further considered in the theory of island biogeography.     

Estimating similarity of communities: a parametric approach to spatio‐temporal analysis of species diversity

Several stochastic models with environmental noise generate spatio‐temporal Gaussian fields of log densities for the species in a community. Combinations of such models for many species often lead to lognormal species abundance distributions. In spatio‐temporal analysis it is often realistic to assume that the same species are expected to occur at different times and/or locations because extinctions are rare events. Spatial and temporal β‐diversity can then be analyzed by studying pairs of communities at different times or locations defined by a bivariate lognormal species abundance model in which a single correlation occurs. This correlation, which is a measure of similarity between two communities, can be estimated from samples even if the sampling intensities vary and are unknown, using the bivariate Poisson lognormal distribution. The estimators are approximately unbiased, although each specific correlation may be rather uncertain when the sampling effort is low with only a small fraction of the species represented in the samples. An important characteristic of this community correlation is that it relates to the classical Jaccard‐ or the Sørensen‐indices of similarity based on the number of species present or absent in two communities. However, these indices calculated from samples of species in a community do not necessarily reflect similarity of the communities because the observed number of species depends strongly on the sampling intensities. Thus, we propose that our community correlation should be considered as an alternative to these indices when comparing similarity of communities. We illustrate the application of the correlation method by computing the similarity between temperate bird communities.     

Biological invasion hotspots: a trait‐based perspective reveals new sub‐continental patterns

Invader traits (including plant growth form) may play an important, and perhaps overlooked, role in determining macroscale patterns of biological invasions and therefore warrant greater consideration in future investigations aimed at understanding these patterns. To assess this need, we used empirical data from a national‐level survey of forest in the contiguous 48 states of the USA to identify geographic hotspots of forest plant invasion for three distinct invasion characteristics: invasive species richness, trait richness (defined as the number of the five following plant growth forms represented by the invasive plants present at a given location: forbs, grasses, shrubs, trees, and vines), and species richness within each growth form. Three key findings emerged. 1) The hotspots identified encompassed from 9 to 23% of the total area of our study region, thereby revealing many forests to be not only invaded, but highly invaded. 2) Substantial spatial disagreement among hotspots of invasive species richness, invasive trait richness, and species richness of invasive plants within each growth form revealed many locations to be hotspots for invader traits, or for particular growth forms of invasive plants, rather than for invasive plants in general. 3) Despite eastern forests exhibiting higher levels of plant invasion than western forests, species richness for invasive forbs and grasses in the west were respectively greater than and equivalent to levels found in the east. Contrasting patterns between eastern and western forests in the number of invasive species detected for each growth form combined with the spatial disagreement found among hotspot types suggests trait‐based variability in invasion drivers. Our findings reveal invader traits to be an important contributor to macroscale invasion patterns.     

Comparison of a culture‐based and a PCR‐based methods for estimating bacterial abundance on eggshells,with comments on statistical analyses

Field ornithologists have used traditional culture‐based techniques to determine the presence and abundance of microbes on surfaces such as eggshells, but culture‐independent PCR‐based methods have recently been introduced. We compared the traditional culture‐based and the real‐time PCR‐based methods for detecting and quantifying Escherichia coli on the eggshells of Eurasian Magpies (Pica pica). PCR estimates of bacterial abundance were ～10 times higher than culture‐based estimates, and the culture‐based technique failed to detect bacteria at lower densities. When both methods detected bacteria, bacterial densities determined by the two methods were positively correlated, indicating that both methods can be used to study factors affecting bacterial densities. The difference between the two methods is consistent with generally acknowledged higher sensitivity of the PCR method, but the extent of the difference in our study (10×) may have been influenced by both a PCR‐based overestimation and culture‐based underestimation of bacterial densities. Our results also illustrate that bacterial counts may sometimes produce left‐censored data (i.e., we did not detect E. coli in 62% of our samples using the culture‐based method). Specific statistical methods have been developed for analyzed left‐censored data, but, to our knowledge, have not been used by ornithologists. In future studies, investigators studying bacterial loads should provide information about the possible degree of left censoring and should justify their choice of statistical methods from the broad set of available methods, including those explicitly designed for censored data.     

Inferring Pongo conservation units: a perspective based on microsatellite and mitochondrial DNA analyses

In order to define evolutionarily significant and management units (ESUs and MUs) among subpopulations of Sumatran (Pongo pygmaeus abelii) and Bornean (P. p. pygmaeus) orangutans we determined their genetic relationships. We analyzed partial sequences of four mitochondrial genes and nine autosomal microsatellite loci of 70 orangutans to test two hypotheses regarding the population structure within Borneo and the genetic distinction between Bornean and Sumatran orangutans. Our data show Bornean orangutans consist of two genetic clusters—the western and eastern clades. Each taxon exhibits relatively distinct mtDNA and nuclear genetic distributions that are likely attributable to genetic drift. These groups, however, do not warrant designations as separate conservation MUs because they demonstrate no demographic independence and only moderate genetic differentiation. Our findings also indicate relatively high levels of overall genetic diversity within Borneo, suggesting that observed habitat fragmentation and erosion during the last three decades had limited influence on genetic variability. Because the mtDNA of Bornean and Sumatran orangutans are not strictly reciprocally monophyletic, we recommend treating these populations as separate MUs and discontinuing inter-island translocation of animals unless absolutely necessary.     

Fungal functional ecology: bringing a trait‐based approach to plant‐associated fungi

Fungi play many essential roles in ecosystems. They facilitate plant access to nutrients and water, serve as decay agents that cycle carbon and nutrients through the soil, water and atmosphere, and are major regulators of macro‐organismal populations. Although technological advances are improving the detection and identification of fungi, there still exist key gaps in our ecological knowledge of this kingdom, especially related to function . Trait‐based approaches have been instrumental in strengthening our understanding of plant functional ecology and, as such, provide excellent models for deepening our understanding of fungal functional ecology in ways that complement insights gained from traditional and ‐omics‐based techniques. In this review, we synthesize current knowledge of fungal functional ecology, taxonomy and systematics and introduce a novel database of fungal functional traits (Fun^Fun). Fun^Fun is built to interface with other databases to explore and predict how fungal functional diversity varies by taxonomy, guild, and other evolutionary or ecological grouping variables. To highlight how a quantitative trait‐based approach can provide new insights, we describe multiple targeted examples and end by suggesting next steps in the rapidly growing field of fungal functional ecology.     

Questioning the mutual benefits of myrmecochory: a stable isotope‐based experimental approach

相似文献