A matrix‐based method of moments for fitting the multivariate random effects model for meta‐analysis and meta‐regression

Multivariate meta‐analysis is becoming more commonly used. Methods for fitting the multivariate random effects model include maximum likelihood, restricted maximum likelihood, Bayesian estimation and multivariate generalisations of the standard univariate method of moments. Here, we provide a new multivariate method of moments for estimating the between‐study covariance matrix with the properties that (1) it allows for either complete or incomplete outcomes and (2) it allows for covariates through meta‐regression. Further, for complete data, it is invariant to linear transformations. Our method reduces to the usual univariate method of moments, proposed by DerSimonian and Laird, in a single dimension. We illustrate our method and compare it with some of the alternatives using a simulation study and a real example.     

Vegetation–environment relationships and classification of the seasonal savannas in Venezuela

The seasonal savannas dominated by the C₄ grasses of the genus Trachypogon, are widespread in northern South America. In Venezuela, they extend from the central lowland Llanos to intermediate elevations in the Coastal and Andean Mountains and to the Guiana Plateau (Gran Sabana) in the south. This study aims to classify these savannas and to understand the environmental factors that determine their composition and structure. Thirty-seven sites were sampled, plant cover and density were measured in 376 one square meter quadrats and the importance value index (IVI) was calculated. Climate data were obtained from climatological stations and soil properties were analyzed. The results were classified by clustering and TWINSPAN. Floristic and environmental data were ordered with the canonical correspondence analysis (CCA).Trachypogon savannas are heterogeneous, both floristically and environmentally. An altitudinal gradient of 2000 m separates the intermediate elevation Coastal Mountains (Type I) and the Guiana savannas (Type II) from the lowland Llanos. In the lowlands, sparsely covered and treeless communities on extremely oligotrophic and sandy soils (Type IV) differ structurally and floristically from woody savannas (Type III). The floristics and structure of the savannas respond directly or indirectly to elevation and water and nutrient availability. These responses were evidenced by: (a) floristic composition, as Neotropical lowland savanna species merged with those of the Andean sub-páramo in Type I savannas or with those from the Guianan flora in Type II savannas. (b) Species richness, which ranged from an average of 13.8 per site in sandy Type IV savannas to 38.9 per site in Type I intermediate elevation savannas. (c) Community physiognomy, which changes from an homogeneous herbaceous matrix with dispersed trees in Type III savannas to a shrubby Type I savannas to “treeless” Types II and IV savannas. (d) Plant cover which varied from 93.8% in the fertile Type I savannas to around 80% in the sandy oligotrophic savannas of Types II and IV. Each savanna type is related to one of the major geomorphological regions of Venezuela.     

Making sense of ultrahigh‐resolution movement data: A new algorithm for inferring sites of interest

Decomposing the life track of an animal into behavioral segments is a fundamental challenge for movement ecology. The proliferation of high‐resolution data, often collected many times per second, offers much opportunity for understanding animal movement. However, the sheer size of modern data sets means there is an increasing need for rapid, novel computational techniques to make sense of these data. Most existing methods were designed with smaller data sets in mind and can thus be prohibitively slow. Here, we introduce a method for segmenting high‐resolution movement trajectories into sites of interest and transitions between these sites. This builds on a previous algorithm of Benhamou and Riotte‐Lambert (2012). Adapting it for use with high‐resolution data. The data’s resolution removed the need to interpolate between successive locations, allowing us to increase the algorithm’s speed by approximately two orders of magnitude with essentially no drop in accuracy. Furthermore, we incorporate a color scheme for testing the level of confidence in the algorithm's inference (high = green, medium = amber, low = red). We demonstrate the speed and accuracy of our algorithm with application to both simulated and real data (Alpine cattle at 1 Hz resolution). On simulated data, our algorithm correctly identified the sites of interest for 99% of “high confidence” paths. For the cattle data, the algorithm identified the two known sites of interest: a watering hole and a milking station. It also identified several other sites which can be related to hypothesized environmental drivers (e.g., food). Our algorithm gives an efficient method for turning a long, high‐resolution movement path into a schematic representation of broadscale decisions, allowing a direct link to existing point‐to‐point analysis techniques such as optimal foraging theory. It is encoded into an R package called SitesInterest , so should serve as a valuable tool for making sense of these increasingly large data streams.     

The ImageJ ecosystem: Open‐source software for image visualization,processing, and analysis

For decades, biologists have relied on software to visualize and interpret imaging data. As techniques for acquiring images increase in complexity, resulting in larger multidimensional datasets, imaging software must adapt. ImageJ is an open‐source image analysis software platform that has aided researchers with a variety of image analysis applications, driven mainly by engaged and collaborative user and developer communities. The close collaboration between programmers and users has resulted in adaptations to accommodate new challenges in image analysis that address the needs of ImageJ's diverse user base. ImageJ consists of many components, some relevant primarily for developers and a vast collection of user‐centric plugins. It is available in many forms, including the widely used Fiji distribution. We refer to this entire ImageJ codebase and community as the ImageJ ecosystem. Here we review the core features of this ecosystem and highlight how ImageJ has responded to imaging technology advancements with new plugins and tools in recent years. These plugins and tools have been developed to address user needs in several areas such as visualization, segmentation, and tracking of biological entities in large, complex datasets. Moreover, new capabilities for deep learning are being added to ImageJ, reflecting a shift in the bioimage analysis community towards exploiting artificial intelligence. These new tools have been facilitated by profound architectural changes to the ImageJ core brought about by the ImageJ2 project. Therefore, we also discuss the contributions of ImageJ2 to enhancing multidimensional image processing and interoperability in the ImageJ ecosystem.     

High‐dimensional data analysis: Selection of variables,data compression and graphics – Application to gene expression

The paper presents effective and mathematically exact procedures for selection of variables which are applicable in cases with a very high dimension as, for example, in gene expression analysis. Choosing sets of variables is an important method to increase the power of the statistical conclusions and to facilitate the biological interpretation. For the construction of sets, each single variable is considered as the centre of potential sets of variables. Testing for significance is carried out by means of the Westfall‐Young principle based on resampling or by the parametric method of spherical tests. The particular requirements for statistical stability are taken into account; each kind of overfitting is avoided. Thus, high power is attained and the familywise type I error can be kept in spite of the large dimension. To obtain graphical representations by heat maps and curves, a specific data compression technique is applied. Gene expression data from B‐cell lymphoma patients serve for the demonstration of the procedures.     

Phosphorylation of NuMA by Aurora‐A kinase in PC‐3 prostate cancer cells affects proliferation,survival, and interphase NuMA localization

Aurora‐A is a serine/threonine kinase that has oncogenic properties in vivo. The expression and kinase activity of Aurora‐A are up‐regulated in multiple malignancies. Aurora‐A is a key regulator of mitosis that localizes to the centrosome from the G2 phase through mitotic exit and regulates mitotic spindle formation as well as centrosome separation. Overexpression of Aurora‐A in multiple malignancies has been linked to higher tumor grade and poor prognosis through mechanisms that remain to be defined. Using an unbiased proteomics approach, we identified the protein nuclear mitotic apparatus (NuMA) as a robust substrate of Aurora‐A kinase. Using a small molecule Aurora‐A inhibitor in conjunction with a reverse in‐gel kinase assay (RIKA), we demonstrate that NuMA becomes hypo‐phosphorylated in vivo upon Aurora‐A inhibition. Using an alanine substitution strategy, we identified multiple Aurora‐A phospho‐acceptor sites in the C‐terminal tail of NuMA. Functional analyses demonstrate that mutation of three of these phospho‐acceptor sites significantly diminished cell proliferation. In addition, alanine mutation at these sites significantly increased the rate of apoptosis. Using confocal immunofluorescence microscopy, we show that the NuMA T1804A mutant mis‐localizes to the cytoplasm in interphase nuclei in a punctate pattern. The identification of Aurora‐A phosphorylation sites in NuMA that are important for cell cycle progression and apoptosis provides new insights into Aurora‐A function. J. Cell. Biochem. 114: 823–830, 2013. © 2012 Wiley Periodicals, Inc.     

Gradient analysis and classification of the woody vegetation for four sites in southern Illinois and adjacent Missouri

The woody vegetation and associated soil-site variables from a range of upland to swamp sites were measured using 480 0.04 ha plots from Little Black Slough, Goose Pond and Horseshoe Lake in Illinois, and Mingo Wildlife Refuge, Missouri. Multiple regression, correlation, and factor analysis were used to relate soil-site data to vegetation structure and composition. Coenoclines of both the understory and overstory were constructed to represent the upland-swamp vegetation gradient of the region near the northern terminus of the southern floodplain forest. Percent sand, depth of flooding, and silt content were variables most strongly related to the understory coenocline. Depth of flooding, and clay content were most strongly related to the overstory coenocline. Beta diversities of the understory and overstory coenoclines were 5.8 and 6.9HC. Understory density and overstory basal area increased and species richness and heterogeneity decreased along the upland-swamp gradient.Classification techniques identified three or four major overstory vegetation types within each study area. The 15 overstory types were ordinated and environmental characteristics summarized for each. Mingo Wildlife Refuge had the least flooding and lowest soil clay content. Classification of all 480 plots from the four study areas identified three major understory groups (mesic, floodplain and swamp) and eight overstory groups. These eight include aQuercus velutina-Q. alba, Quercus rubra-Q. alba, Liquidambar styraciflua-Ulmus americana, Quercus phellos-Q. palustris, Quercus lyrata-Acer rubrum, Acer rubrum-Nyssa aquatica, Nyssa aquatica-Taxodium distichum and aTaxodium distichum-Nyssa aquatica type arranged from upland to swamp.Botanical nomenclature follows Mohlenbrock (1975).Horseshoe Lake and Little Black Slough studies were supported, in part, by McIntire-Stennis Grants to PAR through the Department of Forestry, Southern Illinois University. The Department of Botany, Southern Illinois University provided support for the studies in Goose Pond, Illinois and Mingo Wildlife Refuge, Missouri. We thank Chris Baker and especially Claudia Mitchell for aid in data acquisition and analysis.     

Transformer‐4 version 2.0.1, a free multi‐platform software to quickly reformat genotype matrices of any marker type,and archive them in the Demiurge information system

Transformer‐4 version 2.0.1 (T4) is a multi‐platform freeware programmed in java that can transform a genotype matrix in Excel or XML format into the input formats of one or several of the most commonly used population genetic software, for any possible combination of the populations that the matrix contains. T4 also allows the users to (i) draw allozyme gel interpretations for any number of diploid individuals, and then generate a genotype matrix ready to be used by T4; and (ii) produce basic reports about the data in the matrices. Furthermore, T4 is the only way to optionally submit ‘genetic diversity digests’ for publication in the Demiurge online information system ( http://www.demiurge-project.org ). Each such digest undergoes peer‐review, and it consists of a geo‐referenced data matrix in the tfm4 format plus any ancillary document or hyperlink that the digest authors see fit to include. The complementarity between T4 and Demiurge facilitates a free, safe, permanent, and standardized data archival and analysis system for researchers, and may also be a convenient resource for scientific journals, public administrations, or higher educators. T4 and its converters are freely available (at, respectively, http://www.demiurge-project.org/download_t4 and http://www.demiurge-project.org/converterstore ) upon registration in the Demiurge information system ( http://demiurge-project.org/register ). Users have to click on the link provided on an account validation email, and accept Demiurge's terms of use (see http://www.demiurge-project.org/termsofuse ). A thorough user's guide is available within T4. A 3‐min promotional video about T4 and Demiurge can be seen at http://vimeo.com/29828406 .     

phorest: a web‐based tool for comparative analyses of expressed sequence tag data

Comparative analysis of expressed sequence tags is becoming an important tool in molecular ecology for comparing gene expression in organisms grown in certain environments. Additionally, expressed sequence tag database information can be used for the construction of DNA microarrays and for the detection of single nucleotide polymorphisms. For such applications, we present phorest , a web‐based tool for managing, analysing and comparing various collections of expressed sequence tags. It is written in PHP (PHP: Hypertext Preprocessor) and runs on UNIX, Microsoft Windows and Macintosh (Mac OS X) platforms.     

Furazolidone treatment for Helicobacter Pylori infection: A systematic review and meta‐analysis

Antibiotic resistance is a major cause of Helicobacter pylori (H. pylori) treatment failures. Because the resistance rate of H. pylori to furazolidone is low, we aimed to assess the efficacy and safety of furazolidone. We searched the PubMed, Web of Science, Cochrane Library, and Embase databases and included randomized controlled trials (RCT) that either compared furazolidone to other antibiotics or changed the administered dose of furazolidone. A total of 18 articles were included in the meta‐analysis. According to the intention‐to‐treat (ITT) analysis, the total eradication rates of furazolidone‐containing therapy were superior to those of other antibiotic‐containing therapies (relative risk [RR] 1.07, 95% confidence interval [CI] 1.01‐1.14) (13 RCTs). Specifically, the eradication rates of furazolidone‐containing therapy were better than those for metronidazole‐containing therapy (RR 1.10, 95% CI: 1.01‐1.21 for ITT). The eradication rate of furazolidone‐containing bismuth‐containing quadruple therapy was 92.9% (95% CI: 90.7%‐95.1%) (PP). In addition, a higher daily dose of furazolidone increased the eradication rate (RR 1.17, 95% CI: 1.05‐1.31). And the incidence of some adverse effects, such as fever and anorexia, was higher in the furazolidone group than in the control group, the overall incidences of total side effects and severe side effects showed no significant differences between the groups. Furazolidone‐containing treatments could achieve satisfactory eradication rates and did not increase the incidence of total or severe adverse effects, but the incidence of milder side effects, such as fever and anorexia, should be considered when prescribing furazolidone‐containing treatments to patients.     

PipeCraft: Flexible open‐source toolkit for bioinformatics analysis of custom high‐throughput amplicon sequencing data

High‐throughput sequencing methods have become a routine analysis tool in environmental sciences as well as in public and private sector. These methods provide vast amount of data, which need to be analysed in several steps. Although the bioinformatics may be applied using several public tools, many analytical pipelines allow too few options for the optimal analysis for more complicated or customized designs. Here, we introduce PipeCraft, a flexible and handy bioinformatics pipeline with a user‐friendly graphical interface that links several public tools for analysing amplicon sequencing data. Users are able to customize the pipeline by selecting the most suitable tools and options to process raw sequences from Illumina, Pacific Biosciences, Ion Torrent and Roche 454 sequencing platforms. We described the design and options of PipeCraft and evaluated its performance by analysing the data sets from three different sequencing platforms. We demonstrated that PipeCraft is able to process large data sets within 24 hr. The graphical user interface and the automated links between various bioinformatics tools enable easy customization of the workflow. All analytical steps and options are recorded in log files and are easily traceable.     

A review of thermochemical upgrading of pyrolysis bio‐oil: Techno‐economic analysis,life cycle assessment,and technology readiness

Technologies for upgrading fast pyrolysis bio‐oil to drop‐in fuels and coproducts are under development and show promise for decarbonizing energy supply for transportation and chemicals markets. The successful commercialization of these fuels and the technologies deployed to produce them depend on production costs, scalability, and yield. To meet environmental regulations, pyrolysis‐based biofuels need to adhere to life cycle greenhouse gas intensity standards relative to their petroleum‐based counterparts. We review literature on fast pyrolysis bio‐oil upgrading and explore key metrics that influence their commercial viability through life cycle assessment (LCA) and techno‐economic analysis (TEA) methods together with technology readiness level (TRL) evaluation. We investigate the trade‐offs among economic, environmental, and technological metrics derived from these methods for individual technologies as a means of understanding their nearness to commercialization. Although the technologies reviewed have not attained commercial investment, some have been pilot tested. Predicting the projected performance at scale‐up through models can, with industrial experience, guide decision‐making to competitively meet energy policy goals. LCA and TEA methods that ensure consistent and reproducible models at a given TRL are needed to compare alternative technologies. This study highlights the importance of integrated analysis of multiple economic, environmental, and technological metrics for understanding performance prospects and barriers among early stage technologies.     

CellShape: A user‐friendly image analysis tool for quantitative visualization of bacterial cell factories inside

Visualization of the intracellular constituents of individual bacteria while performing as live biocatalysts is in principle doable through more or less sophisticated fluorescence microscopy. Unfortunately, rigorous quantitation of the wealth of data embodied in the resulting images requires bioinformatic tools that are not widely extended within the community‐let alone that they are often subject to licensing that impedes software reuse. In this context we have developed CellShape, a user‐friendly platform for image analysis with subpixel precision and double‐threshold segmentation system for quantification of fluorescent signals stemming from single‐cells. CellShape is entirely coded in Python, a free, open‐source programming language with widespread community support. For a developer, CellShape enhances extensibility (ease of software improvements) by acting as an interface to access and use existing Python modules; for an end‐user, CellShape presents standalone executable files ready to open without installation. We have adopted this platform to analyse with an unprecedented detail the tridimensional distribution of the constituents of the gene expression flow (DNA, RNA polymerase, mRNA and ribosomal proteins) in individual cells of the industrial platform strain Pseudomonas putida KT2440. While the CellShape first release version (v0.8) is readily operational, users and/or developers are enabled to expand the platform further.     

Restoration ecology of riverine wetlands: A 5-year post-operation survey on the Rhône River, France

Bibliographical study of articles published in scientific journals over the last 10 years, and of books published over the last 20 years, reveals a clear increase in the number of publications dealing with ecological engineering, particularly on aquatic ecosystems, which today are becoming a major topic. The concept of ecological restoration must be clearly defined scientifically and include adequate pre- and post-restoration monitoring of various performance indicators, to allow for restoration, evaluation and increase its success. A restoration experiment was carried out in a former channel of the Rhône River according to a scientifically based decision framework. Long-term monitoring of aquatic vegetation (17 years of data) on two former channels (reference and restored ecosystem) clearly demonstrated human impacts on aquatic ecosystems. A channel exhibiting rapid terrestrialization and eutrophication processes after completion of a hydroelectric scheme construction was restored. In keeping with the hypothesis, the increase in groundwater supply led the restored ecosystem to return to a less advanced and self-sustainable successional stage, whereas vegetation monitoring in the reference channel did not show significant changes over this 17-year of period, supporting long-term studies to determine the effects of restoration on the biota.     

A Simple Two‐Sample Rank Test for Multivariate Survival Outcomes with Left Truncation and Right Censoring

A distribution‐free two‐sample rank test is proposed for testing for differences between survival distributions in the analysis of biomedical studies in which two groups of subjects are followed over time for a particular outcome, which may recur. This method is motivated by an observational HIV (human immunodeficiency virus) study in which a group of HIV‐seropositive women and a comparable group of HIV‐seronegative women were examined every 6 months for the presence of cervical intraepithelial neoplasia (CIN), the cervical cancer precursor. Women entered the study serially and were subject to random loss to follow‐up. Only women free of CIN at study entry were followed resulting in left‐truncated survival times. If a woman is found to be CIN infected at a later examination, she is treated and then followed until CIN recurs. The two groups of women were compared at both occurrences of CIN on the basis of rank statistics. For the first occurrence of CIN, survival times since the beginning of the study (based on calendar time) are compared. For a recurrence of CIN, survival times since the first development of CIN are compared. The proposed test statistic for an overall difference between the two groups follows a chi‐square distribution with two degrees of freedom. Simulation results demonstrate the usefulness of the proposed test proposed test statistic, which reduces to the Gehan statistic if each person is followed only to the first failure and there is no serial enrollment.     

4‐alkoxyethoxy‐N‐octadecyl‐1,8‐naphthalimide fluorescent sensor for human serum albumin and other major blood proteins: design,synthesis and solvent effect

A series of 4‐alkoxyethoxy‐N‐octadecyl‐1,8‐naphthalimides with intense blue fluorescence were designed and synthesized as polarity and spectrofluorimetric probes for the determination of proteins. In solvents of different polarities, the Stokes shifts of two dyes increased with increasing solvent polarity and fluorescence quantum yields decreased significantly, suggesting that electronic transiting from ground to excited states was π–π^* in character. Dipole moment changes were estimated from solvent‐dependent Stokes shift data using a solvatochromic method based on bulk solvent polarity functions and the microscopic solvent polarity parameter (). These results were generally consistent with semi‐empirical molecular orbital calculations and were found to be quite reliable based on the fact that the correlation of the solvatochromic Stokes shifts with was superior to that obtained using bulk solvent polarity functions. Fluorescence data revealed that the fluorescence quenching of human serum albumin (HSA) by dyes was the result of the formation of a Dye–HSA complex. The method was applied to the determination of total proteins (HSA + immunoglobulins) in human serum samples and results were in good agreement with those reported by the research institute. Copyright © 2012 John Wiley & Sons, Ltd.     

Effect of land‐use and land‐cover change on mangrove blue carbon: A systematic review

Mangroves shift from carbon sinks to sources when affected by anthropogenic land‐use and land‐cover change (LULCC). Yet, the magnitude and temporal scale of these impacts are largely unknown. We undertook a systematic review to examine the influence of LULCC on mangrove carbon stocks and soil greenhouse gas (GHG) effluxes. A search of 478 data points from the peer‐reviewed literature revealed a substantial reduction of biomass (82% ± 35%) and soil (54% ± 13%) carbon stocks due to LULCC. The relative loss depended on LULCC type, time since LULCC and geographical and climatic conditions of sites. We also observed that the loss of soil carbon stocks was linked to the decreased soil carbon content and increased soil bulk density over the first 100 cm depth. We found no significant effect of LULCC on soil GHG effluxes. Regeneration efforts (i.e. restoration, rehabilitation and afforestation) led to biomass recovery after ~40 years. However, we found no clear patterns of mangrove soil carbon stock re‐establishment following biomass recovery. Our findings suggest that regeneration may help restore carbon stocks back to pre‐disturbed levels over decadal to century time scales only, with a faster rate for biomass recovery than for soil carbon stocks. Therefore, improved mangrove ecosystem management by preventing further LULCC and promoting rehabilitation is fundamental for effective climate change mitigation policy.