Repetitive flanking sequences (ReFS): novel molecular markers from microsatellite families

Although microsatellite markers have become exceedingly popular in molecular studies of wild organisms, their development in some taxonomic groups is challenging. This is partly because of repetitive flanking sequences, which lead to the simultaneous amplification of alleles from multiple loci. Until now, these microsatellite DNA families have been considered unsuitable for population genetics studies, but here we describe our development of these repetitive flanking sequences (ReFS) as novel molecular markers. We illustrate the utility of these markers by using them to address an outstanding taxonomic question in the moth genus Schrankia.     

Recent advances in N- and C-terminus cysteine protein bioconjugation

Advances in the site-specific chemical modification of proteins, also referred to as protein bioconjugation, have proved instrumental in revolutionary approaches to designing new protein-based therapeutics. Of the sites available for protein modification, cysteine residues or the termini of proteins have proved especially popular owing to their favorable properties for site-specific modification. Strategies that, therefore, specifically target cysteine at the termini offer a combination of these favorable properties of cysteine and termini bioconjugation. In this review, we discuss these strategies with a particular focus on those reported recently and provide our opinion on the future direction of the field.     

Behaviour of simple population models under ecological processes

The two most popular and extensively-used discrete models of population growth display the generic bifurcation structure of a hierarchy of period-doubling sequence to chaos with increasing growth rates. In this paper we show that these two models, though they belong to a general class of one-dimensional maps, show very different dynamics when important ecological processes such as immigration and emigration/depletion, are considered. It is important that ecologists recognize the differences between these models before using them to describe their data—or develop optimization strategies—based on these models.     

Recent advances in research on fibronectin and other cell attachment proteins

Fibronectin and other cell attachment proteins provide molecular models for beginning to unravel the complex interactions of the cell surface with the extracellular matrix. This area has been reviewed in considerable detail previously [1–10]. Our brief review will therefore be selective rather than comprehensive, and it will focus on some recent generalizations about this class of proteins, as well as on recent advances in the molecular analysis of the functions of these proteins and their receptors. we shall also present various popular or provocative hypotheses and speculations about future work in the field.     

Recent progress on developing exogenous monocyte/macrophage-based therapies for inflammatory and degenerative diseases

Cell-based therapies are a rapidly developing area of regenerative medicine as dynamic treatments that execute therapeutic functions multimodally. Monocytes and macrophages, as innate immune cells that control inflammation and tissue repair, are increasing popular clinical candidates due to their spectrum of functionality. In this article, we review the role of monocytes and macrophages specifically in inflammatory and degenerative disease pathology and the evidence supporting the use of these cells as an effective therapeutic strategy. We compare current strategies of exogenously polarized monocyte/macrophage therapies regarding dosage, delivery and processing to identify outcomes, advances and challenges to their clinical use. Monocytes/macrophages hold the potential to be a promising therapeutic avenue but understanding and optimization of disease-specific efficacy is needed to accelerate their clinical use.     

Replication-competent retroviral vectors for expressing genes in avian cells in vitro and in vivo

Replication-competent retroviral vectors based on Rous sarcoma virus (RSV) are becoming increasingly popular for expressing genes in both primary cell cultures and embryonic chick tissuesin ovo. In this article, we review the features of RSV and its life cycle that make it suitable for use as a vector. We describe the design and use of the RCAS and RCAS(BP) series of vectors, which are currently the most widely used RSV-based vectors, illustrating both their strengths and weaknesses. Finally, we outline laboratory protocols suitable for the handling of these retroviral vectors.     

蛋白组学解析拟南芥响应细菌信号分子N-3-oxo-hexanoyl-homoserine-lactone（OHHL）的机制

细菌来源的群体感应信号分子能诱导与调控植物的抗病性与生长发育,本文用细菌群体感应信号分子N一3-oxo—hexanoyl-homoserine—lactone（OHHL）对拟南芥进行不同时间的处理,提取蛋白进行双向电泳分析,用蛋白组学的方法解析拟南芥响应细菌信号分子的机制。双向电泳与质谱分析共鉴定出47个点,这些蛋白中随处理时间的增加表达量上调的蛋白点数目增加,并且与植物抗氧化、物质代谢和细胞信号转导密切相关。因此通过蛋白组学分析结果可以更好的解释植物与细菌的相互作用机制,进一步利用其之间的联系来促进植物更好的生长发育。     

Analyzing time series gene expression data

MOTIVATION: Time series expression experiments are an increasingly popular method for studying a wide range of biological systems. However, when analyzing these experiments researchers face many new computational challenges. Algorithms that are specifically designed for time series experiments are required so that we can take advantage of their unique features (such as the ability to infer causality from the temporal response pattern) and address the unique problems they raise (e.g. handling the different non-uniform sampling rates). RESULTS: We present a comprehensive review of the current research in time series expression data analysis. We divide the computational challenges into four analysis levels: experimental design, data analysis, pattern recognition and networks. For each of these levels, we discuss computational and biological problems at that level and point out some of the methods that have been proposed to deal with these issues. Many open problems in all these levels are discussed. This review is intended to serve as both, a point of reference for experimental biologists looking for practical solutions for analyzing their data, and a starting point for computer scientists interested in working on the computational problems related to time series expression analysis.     

Discovering functional small molecules in the gut microbiome

The human microbiome has emerged as a source of bacterially produced, functional small molecules that help regulate health and disease, and their discovery and annotation has become a popular research topic. Identifying these molecules provides an essential step in unraveling the molecular mechanisms underlying biological outcomes. The relevance of specific bacterial members of the microbiome has been demonstrated in a variety of correlative studies, and there are many possible paths from these correlations to the responsible metabolites. Herein, we summarize two studies that have recently identified gut microbiome metabolites that modulate immune responses or promote physical activity. Aside from the deep insights gained, these studies provide blueprints for successfully uncovering the molecules and mechanisms that control important physiological pathways.     

Conservation successes at micro-, meso- and macroscales

Although large-scale biodiversity declines are ongoing, certain conservation actions have made a positive difference. Rates of extinction and endangerment of vertebrate species, for instance, have probably been reduced via conservation interventions. Such conservation actions operate at different spatial scales. Habitat preservation and endangered species recovery are examples of conservation successes at microscales. Mesoscale conservation includes regional cooperation among neighboring countries that has arrested population declines of endangered species, such as mountain gorillas. At macroscales, public pressure on multinational corporations has sometimes resulted in their abandoning environmentally damaging practices or suppliers with poor environmental records. Overall, conservation projects such as these need more long-term funding and greater political and popular support, and must also include provisions to evaluate and document their outcomes. As we discuss here, a focus on conservation successes achieved at different scales can help to promote these aims and guide future conservation victories.     

The home-range concept: are traditional estimators still relevant with modern telemetry technology?

Recent advances in animal tracking and telemetry technology have allowed the collection of location data at an ever-increasing rate and accuracy, and these advances have been accompanied by the development of new methods of data analysis for portraying space use, home ranges and utilization distributions. New statistical approaches include data-intensive techniques such as kriging and nonlinear generalized regression models for habitat use. In addition, mechanistic home-range models, derived from models of animal movement behaviour, promise to offer new insights into how home ranges emerge as the result of specific patterns of movements by individuals in response to their environment. Traditional methods such as kernel density estimators are likely to remain popular because of their ease of use. Large datasets make it possible to apply these methods over relatively short periods of time such as weeks or months, and these estimates may be analysed using mixed effects models, offering another approach to studying temporal variation in space-use patterns. Although new technologies open new avenues in ecological research, our knowledge of why animals use space in the ways we observe will only advance by researchers using these new technologies and asking new and innovative questions about the empirical patterns they observe.     

Statistical inference and power analysis for direct and spillover effects in two-stage randomized experiments

Two-stage randomized experiments become an increasingly popular experimental design for causal inference when the outcome of one unit may be affected by the treatment assignments of other units in the same cluster. In this paper, we provide a methodological framework for general tools of statistical inference and power analysis for two-stage randomized experiments. Under the randomization-based framework, we consider the estimation of a new direct effect of interest as well as the average direct and spillover effects studied in the literature. We provide unbiased estimators of these causal quantities and their conservative variance estimators in a general setting. Using these results, we then develop hypothesis testing procedures and derive sample size formulas. We theoretically compare the two-stage randomized design with the completely randomized and cluster randomized designs, which represent two limiting designs. Finally, we conduct simulation studies to evaluate the empirical performance of our sample size formulas. For empirical illustration, the proposed methodology is applied to the randomized evaluation of the Indian National Health Insurance Program. An open-source software package is available for implementing the proposed methodology.     

The molecular basis for inhibition of sulindac and its metabolites towards human aldose reductase

Sulindac (SLD) exhibits both the highest inhibitory activity towards human aldose reductase (AR) among popular non-steroidal anti-inflammatory drugs and clear beneficial clinical effects on Type 2 diabetes. However, the molecular basis for these properties is unclear. Here, we report that SLD and its pharmacologically active/inactive metabolites, SLD sulfide and SLD sulfone, are equally effective as un-competitive inhibitors of AR in vitro. Crystallographic analysis reveals that π-π stacking favored by the distinct scaffold of SLDs is pivotal to their high AR inhibitory activities. These results also suggest that SLD sulfone could be a potent lead compound for AR inhibition in vivo.     

A novel approach to fold recognition using sequence-derived properties from sets of structurally similar local fragments of proteins

Comparative modeling methods can consistently produce reliable structural models for protein sequences with more than 25% sequence identity to proteins with known structure. However, there is a good chance that also sequences with lower sequence identity have their structural components represented in structural databases. To this end, we present a novel fragment-based method using sets of structurally similar local fragments of proteins. The approach differs from other fragment-based methods that use only single backbone fragments. Instead, we use a library of groups containing sets of sequence fragments with geometrically similar local structures and extract sequence related properties to assign these specific geometrical conformations to target sequences. We test the ability of the approach to recognize correct SCOP folds for 273 sequences from the 49 most popular folds. 49% of these sequences have the correct fold as their top prediction, while 82% have the correct fold in one of the top five predictions. Moreover, the approach shows no performance reduction on a subset of sequence targets with less than 10% sequence identity to any protein used to build the library.     

Decrease in uptake of arachidonic acid by indomethacin in LS174T human colon cancer cells; a novel cyclooxygenase-2-inhibition-independent effect

Nonsteroidal anti-inflammatory drugs (NSAIDs) have chemopreventive activity and may be suitable for treatment of colorectal cancer. A popular and potent NSAID, indomethacin, is known to cause serious side-effects, for this reason its therapeutic usefulness is limited. However, these side-effects are likely to be attributed to the additional effects of indomethacin besides its cyclooxygenase inhibition. In this study, we examined the effect of indomethacin on arachidonic acid uptake using LS174T human colon cancer cells. We here show that treatment of LS174T cells with indomethacin reduced arachidonic acid uptake as well as reduced expressions of fatty acid translocase/CD36 and peroxisome proliferators-activated receptor γ. Since arachidonic acid is a major substrate of inflammatory mediators such as prostaglandins and leukotrienes, we believe this novel effect of indomethacin may apply to new treatment strategies that aim to suppress these mediators by decreasing the uptake of their substrates, which would eventually inhibit colorectal cancer malignancy.     

A Mutual Interest? Ethnography in Anthropology and Cultural Studies

Anthropology and cultural studies share a concern with ethnographic method. Cultural studies increasingly uses ethnography in its analyses of popular culture as it seeks to balance earlier preoccupations with text. Where cultural studies diverges from anthropology is in its encompassment within an oppositional paradigm which embeds a political agenda deep in its ethnographic work. This paper uses the area of media to explore the ways in which ethnography has been adopted and developed in cultural studies. Ethnographic focus has shifted interest in media from the text to the reception of media products. At the same time, the oppositional legacy from cultural studies' earliest days has tended to produce rather romanticised findings of a subaltern audience using media products to resist dominant cultural and political structures. It is suggested that anthropology should pay attention to cultural studies use of ethnographic method, first taking seriously the ground of popular culture as a challenge for anthropologists' more extended use of ethnography. But second, we should pay attention to the problem silences in cultural studies' ethnographies—silences like racism in audiences—since these may well have at least part of their basis in the method itself.     

Controllable surface modification of poly(lactic-co-glycolic acid) (PLGA) by hydrolysis or aminolysis I: physical, chemical, and theoretical aspects

While biodegradable, biocompatible polyesters such as poly (lactic-co-glycolic acid) (PLGA) are popular materials for the manufacture of tissue engineering scaffolds, their surface properties are not particularly suitable for directed tissue growth. Although a number of approaches to chemically modify the PLGA surface have been reported, their applicability to soft tissue scaffolds, which combine large volumes, complex shapes, and extremely fine structures, is questionable. In this paper, we describe two wet-chemical methods, base hydrolysis and aminolysis, to introduce useful levels of carboxylic acid or primary and secondary amine groups, respectively, onto the surface of PLGA with minimal degradation. The effects of temperature, concentration, pH, and solvent type on the kinetics of these reactions are studied by following changes in the wettability of the PLGA using contact angle measurements. In addition, the treated surfaces are studied using X-ray photoelectron spectroscopy (XPS) to determine the effect on the surface chemical structure. Furthermore, we show using XPS analysis that these carboxyl and amine groups are readily activated to allow the covalent attachment of biological macromolecules.     

Photodegradation products of propranolol: the structures and pharmacological studies

Recently, single-dose drug packaging systems, allowing the administration of multiple drugs in a single pill, have become popular for the convenience of the patient. The quality of drugs and an accurate measurement of their photostabilities within this system, however, have not been carefully addressed. Drugs that are unstable in light should be carefully handled to protect their potency and ensure their safety. Propranolol (1), a beta-adrenergic receptor antagonist, is widely used for angina pectoris, arrhythmia, and hypertension. Due to its naphthalene skeleton, this drug may be both light unstable and a photosensitizing agent. In this study, we isolated three photodegraded products of propranolol (1): 1-naphthol (2), N-acetylpropranolol (3), and N-formylpropranolol (4). The structures of these compounds were determined by spectroscopic methods and chemical syntheses. We also examined the acute toxicities of these substances in mice and their binding to beta-adrenergic receptors using rat cerebellum cortex membranes. Although the photoproducts isolated in this study did not exhibit any acute toxicity or significant binding to beta-adrenergic receptors, these results serve as a warning to single-dose packaging systems, as propranolol (1) must be handled carefully to protect the compound from light-induced degradation.     

Strategies for analysing missing item response data with an application to lung cancer

Missing data problems persist in many scientific investigations. Although various strategies for analyzing missing data have been proposed, they are mainly limited to data on continuous measurements. In this paper, we focus on implementing some of the available strategies to analyze item response data. In particular, we investigate the effects of popular missing data methods on various missing data mechanisms. We examine large sample behaviors of estimators in a simulation study that evaluates and compares their performance. We use data from a quality of life study with lung cancer patients to illustrate the utility of these methods.     

Memes: A motif analysis environment in R using tools from the MEME Suite

Identification of biopolymer motifs represents a key step in the analysis of biological sequences. The MEME Suite is a widely used toolkit for comprehensive analysis of biopolymer motifs; however, these tools are poorly integrated within popular analysis frameworks like the R/Bioconductor project, creating barriers to their use. Here we present memes, an R package that provides a seamless R interface to a selection of popular MEME Suite tools. memes provides a novel “data aware” interface to these tools, enabling rapid and complex discriminative motif analysis workflows. In addition to interfacing with popular MEME Suite tools, memes leverages existing R/Bioconductor data structures to store the multidimensional data returned by MEME Suite tools for rapid data access and manipulation. Finally, memes provides data visualization capabilities to facilitate communication of results. memes is available as a Bioconductor package at https://bioconductor.org/packages/memes, and the source code can be found at github.com/snystrom/memes.