The 50 most-cited articles in F1000Research, 2016

High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomic studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Various quantification approaches have been proposed, ranging from simple counting of reads that overlap given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over transcript-level analyses, in terms of performance and interpretability. We also illustrate that the presence of differential isoform usage can lead to inflated false discovery rates in differential gene expression analyses on simple count matrices but that this can be addressed by incorporating offsets derived from transcript-level abundance estimates. We also show that the problem is…

Single-cell RNA sequencing (scRNA-seq) is widely used to profile the transcriptome of individual cells. This provides biological resolution that cannot be matched by bulk RNA sequencing, at the cost of increased technical noise and data complexity. The differences between scRNA-seq and bulk RNA-seq data mean that the analysis of the former cannot be performed by recycling bioinformatics pipelines for the latter. Rather, dedicated single-cell methods are required at various steps to exploit the cellular resolution while accounting for technical noise. This article describes a computational workflow for low-level analyses of scRNA-seq data, based primarily on software packages from the open-source Bioconductor project. It covers basic steps including quality control, data exploration and normalization, as well as more complex procedures such as cell cycle phase assignment, identification of highly variable and correlated genes, clustering into subpopulations and marker gene detection. Analyses were demonstrated on gene-level count data from several publicly available datasets…

In recent years, RNA sequencing (RNA-seq) has become a very widely used technology for profiling gene expression. One of the most common aims of RNA-seq profiling is to identify genes or molecular pathways that are differentially expressed (DE) between two or more biological conditions. This article demonstrates a computational workflow for the detection of DE genes and pathways from RNA-seq data by providing a complete analysis of an RNA-seq experiment profiling epithelial cell subsets in the mouse mammary gland. The workflow uses R software packages from the open-source Bioconductor project and covers all steps of the analysis pipeline, including alignment of read sequences, data exploration, differential expression analysis, visualization and pathway analysis. Read alignment and count quantification is conducted using the Rsubread package and the statistical analyses are performed using the edgeR package. The differential expression analysis uses the quasi-likelihood functionality of edgeR.

High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level of analysis of complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or OTU composition of communities in different conditions. The sequencing reads have to be denoised and assigned to the closest taxa from a reference database. Common approaches use a notion of 97% similarity and normalize the data by subsampling to equalize library sizes. In this paper, we show that statistical models allow more accurate abundance estimates. By providing a complete workflow in R, we enable the user to do sophisticated downstream statistical analyses, whether parametric or nonparametric. We provide examples of using the R packages dada2, phyloseq, DESeq2, ggplot2 and vegan to filter, visualize and test microbiome data. We also provide examples of supervised analyses using random forests and nonparametric testing using community networks and the ggnetwork package.

Plants in their natural habitats adapt to drought stress in the environment through a variety of mechanisms, ranging from transient responses to low soil moisture to major survival mechanisms of escape by early flowering in absence of seasonal rainfall. However, crop plants selected by humans to yield products such as grain, vegetable, or fruit in favorable environments with high inputs of water and fertilizer are expected to yield an economic product in response to inputs. Crop plants selected for their economic yield need to survive drought stress through mechanisms that maintain crop yield. Studies on model plants for their survival under stress do not, therefore, always translate to yield of crop plants under stress, and different aspects of drought stress response need to be emphasized. The crop plant model rice ( Oryza sativa) is used here as an example to highlight mechanisms and genes for adaptation of crop plants to drought stress.

Single-cell RNA sequencing (scRNA-seq) is widely used to profile the transcriptome of individual cells. This provides biological resolution that cannot be matched by bulk RNA sequencing, at the cost of increased technical noise and data complexity. The differences between scRNA-seq and bulk RNA-seq data mean that the analysis of the former cannot be performed by recycling bioinformatics pipelines for the latter. Rather, dedicated single-cell methods are required at various steps to exploit the cellular resolution while accounting for technical noise. This article describes a computational workflow for low-level analyses of scRNA-seq data, based primarily on software packages from the open-source Bioconductor project. It covers basic steps including quality control, data exploration and normalization, as well as more complex procedures such as cell cycle phase assignment, identification of highly variable and correlated genes, clustering into subpopulations and marker gene detection. Analyses were demonstrated on gene-level count data from several publicly available data sets…

Here we present the Cytoscape app version of our association network inference tool CoNet. Though CoNet was developed with microbial community data from sequencing experiments in mind, it is designed to be generic and can detect associations in any data set where biological entities (such as genes, metabolites or species) have been observed repeatedly. The CoNet app supports Cytoscape 2.x and 3.x and offers a variety of network inference approaches, which can also be combined. Here we briefly describe its main features and illustrate its use on microbial count data obtained by 16S rDNA sequencing of arctic soil samples. The CoNet app is available at: http://apps.cytoscape.org/apps/conet.

The ability to easily and efficiently analyse RNA-sequencing data is a key strength of the Bioconductor project. Starting with counts summarised at the gene-level, a typical analysis involves pre-processing, exploratory data analysis, differential expression testing and pathway analysis with the results obtained informing future experiments and validation studies. In this workflow article, we analyse RNA-sequencing data from the mouse mammary gland, demonstrating use of the popular edgeR package to import, organise, filter and normalise the data, followed by the limma package with its voom method, linear modelling and empirical Bayes moderation to assess differential expression and perform gene set testing. This pipeline is further enhanced by the Glimma package which enables interactive exploration of the results so that individual samples and genes can be examined by the user. The complete analysis offered by these three packages highlights the ease with which researchers can turn the raw counts from an RNA-sequencing experiment into biological insights using Bioconductor.

Calculating solvent accessible surface areas (SASA) is a run-of-the-mill calculation in structural biology. Although there are many programs available for this calculation, there are no free-standing, open-source tools designed for easy tool-chain integration. FreeSASA is an open source C library for SASA calculations that provides both command-line and Python interfaces in addition to its C API. The library implements both Lee and Richards' and Shrake and Rupley's approximations, and is highly configurable to allow the user to control molecular parameters, accuracy and output granularity. It only depends on standard C libraries and should therefore be easy to compile and install on any platform. The library is well-documented, stable and efficient. The command-line interface can easily replace closed source legacy programs, with comparable or better accuracy and speed, and with some added functionality.

Ongoing debates surrounding Open Access to the scholarly literature are multifaceted and complicated by disparate and often polarised viewpoints from engaged stakeholders. At the current stage, Open Access has become such a global issue that it is critical for all involved in scholarly publishing, including policymakers, publishers, research funders, governments, learned societies, librarians, and academic communities, to be well-informed on the history, benefits, and pitfalls of Open Access. In spite of this, there is a general lack of consensus regarding the potential pros and cons of Open Access at multiple levels. This review aims to be a resource for current knowledge on the impacts of Open Access by synthesizing important research in three major areas: academic, economic and societal. While there is clearly much scope for additional research, several key trends are identified, including a broad citation advantage for researchers who publish openly, as well as additional benefits to the non-academic dissemination of their work. The economic impact of Open Access is less…

Chronic low back pain (CLBP) is a chronic pain syndrome in the lower back region, lasting for at least 3 months. CLBP represents the second leading cause of disability worldwide being a major welfare and economic problem. The prevalence of CLBP in adults has increased more than 100% in the last decade and continues to increase dramatically in the aging population, affecting both men and women in all ethnic groups, with a significant impact on functional capacity and occupational activities. It can also be influenced by psychological factors, such as stress, depression and/or anxiety. Given this complexity, the diagnostic evaluation of patients with CLBP can be very challenging and requires complex clinical decision-making. Answering the question "what is the pain generator" among the several structures potentially involved in CLBP is a key factor in the management of these patients, since a mis-diagnosis can generate therapeutical mistakes. Traditionally, the notion that the etiology of 80% to 90% of LBP cases is unknown has been mistaken perpetuated across decades. In most cases,…

Networks often contain regions of tightly connected nodes, or clusters, that highlight their shared relationships. An effective way to create a visual summary of a network is to identify clusters and annotate them with an enclosing shape and a summarizing label. Cytoscape provides the ability to annotate a network with shapes and labels, however these annotations must be created manually one at a time, which can be a laborious process. AutoAnnotate is a Cytoscape 3 App that automates the process of identifying clusters and visually annotating them. It greatly reduces the time and effort required to fully annotate clusters in a network, and provides freedom to experiment with different strategies for identifying and labelling clusters. Many customization options are available that enable the user to refine the generated annotations as required. Annotated clusters may be collapsed into single nodes using the Cytoscape groups feature, which helps simplify a network by making its overall structure more visible. AutoAnnotate is applicable to any type of network, including enrichment…

Seven ligands bind to and activate the mammalian epidermal growth factor (EGF) receptor (EGFR/ERBB1/HER1): EGF, transforming growth factor-alpha (TGFA), heparin-binding EGF-like growth factor (HBEGF), betacellulin (BTC), amphiregulin (AREG), epiregulin (EREG), and epigen (EPGN). Of these, EGF, TGFA, HBEGF, and BTC are thought to be high-affinity ligands, whereas AREG, EREG, and EPGN constitute low-affinity ligands. This focused review is meant to highlight recent studies related to actions of the individual EGFR ligands, the interesting biology that has been uncovered, and relevant advances related to ligand interactions with the EGFR.

In the 1990s several biocontrol agents on that contained Burkholderia strains were registered by the United States Environmental Protection Agency (EPA). After risk assessment these products were withdrawn from the market and a moratorium was placed on the registration of Burkholderia-containing products, as these strains may pose a risk to human health. However, over the past few years the number of novel Burkholderia species that exhibit plant-beneficial properties and are normally not isolated from infected patients has increased tremendously. In this commentary we wish to summarize recent efforts that aim at discerning pathogenic from beneficial Burkholderia strains.

Prenatal substance use is a critical public health concern that is linked with several harmful maternal and fetal consequences. The most frequently used substance in pregnancy is tobacco, followed by alcohol, cannabis and other illicit substances. Unfortunately, polysubstance use in pregnancy is common, as well as psychiatric comorbidity, environmental stressors, and limited and disrupted parental care, all of which can compound deleterious maternal and fetal outcomes. There are few existing treatments for prenatal substance use and these mainly comprise behavioral and psychosocial interventions. Contingency management has been shown to be the most efficacious of these. The purpose of this review is to examine the recent literature on the prenatal use of tobacco, alcohol, cannabis, stimulants, and opioids, including the effects of these on maternal and fetal health and the current therapeutic options.

The scientific credibility of findings from clinical trials can be undermined by a range of problems including missing data, endpoint switching, data dredging, and selective publication. Together, these issues have contributed to systematically distorted perceptions regarding the benefits and risks of treatments. While these issues have been well documented and widely discussed within the profession, legislative intervention has seen limited success. Recently, a method was described for using a blockchain to prove the existence of documents describing pre-specified endpoints in clinical trials. Here, we extend the idea by using smart contracts - code, and data, that resides at a specific address in a blockchain, and whose execution is cryptographically validated by the network - to demonstrate how trust in clinical trials can be enforced and data manipulation eliminated. We show that blockchain smart contracts provide a novel technological solution to the data manipulation problem, by acting as trusted administrators and providing an immutable record of trial history.

Biotechnological advances in sequencing have led to an explosion of publicly available data via large international consortia such as The Cancer Genome Atlas (TCGA), The Encyclopedia of DNA Elements (ENCODE), and The NIH Roadmap Epigenomics Mapping Consortium (Roadmap). These projects have provided unprecedented opportunities to interrogate the epigenome of cultured cancer cell lines as well as normal and tumor tissues with high genomic resolution. The Bioconductor project offers more than 1,000 open-source software and statistical packages to analyze high-throughput genomic data. However, most packages are designed for specific data types (e.g. expression, epigenetics, genomics) and there is no one comprehensive tool that provides a complete integrative analysis of the resources and data provided by all three public projects. A need to create an integration of these different analyses was recently proposed. In this workflow, we provide a series of biologically focused integrative analyses of different molecular data. We describe how to download, process and prepare TCGA data and by…

The discovery of the myofibroblast has allowed definition of the cell responsible for wound contraction and for the development of fibrotic changes. This review summarizes the main features of the myofibroblast and the mechanisms of myofibroblast generation. Myofibroblasts originate from a variety of cells according to the organ and the type of lesion. The mechanisms of myofibroblast contraction, which appear clearly different to those of smooth muscle cell contraction, are described. Finally, we summarize the possible strategies in order to reduce myofibroblast activities and thus influence several pathologies, such as hypertrophic scars and organ fibrosis.

Thyroid scintigraphy is now rarely used in the work-up of a thyroid nodule except in the presence of a low TSH value. Therefore, autonomously functioning thyroid nodules (AFTNs) with a normal TSH value are diagnosed only in the rare medical centers that continue to use thyroid scan systematically in the presence of a thyroid nodule. In this review, we discuss the prevalence of AFTN with a normal TSH level and the possible consequences of performing fine needle aspiration cytology (FNAC) in an undiagnosed AFTN. We also discuss the risk of malignant AFTN which may be higher than previously stated.

Diabetes has become one of the largest global health-care problems of the 21 (st) century. According to the Centers for Disease Control and Prevention, the population prevalence of diabetes in the US is approaching 10% and is increasing by 5% each year. Diabetic neuropathy is the most common complication associated with diabetes mellitus. Diabetes causes a broad spectrum of neuropathic complications, including acute and chronic forms affecting each level of the peripheral nerve, from the root to the distal axon. This review will focus on the most common form, distal symmetric diabetic polyneuropathy. There has been an evolution in our understanding of the pathophysiology and the management of diabetic polyneuropathy over the past decade. We highlight these new perspectives and provide updates from the past decade of research.

In reproductive medicine little progress has been achieved regarding the clinical management of patients with a reduced ovarian reserve or poor ovarian response (POR) to stimulation with exogenous gonadotropins -a frustrating experience for clinicians as well as patients. Despite the efforts to optimize the definition of this subgroup of patients, the existing POR criteria unfortunately comprise a heterogeneous population and, importantly, do not offer any recommendations for clinical handling. Recently, the POSEIDON group ( P atient- O riented S trategies E ncompassing I ndividualize D O ocyte N umber) proposed a new stratification of assisted reproductive technology (ART) in patients with a reduced ovarian reserve or unexpected inappropriate ovarian response to exogenous gonadotropins. In brief, four subgroups have been suggested based on quantitative and qualitative parameters, namely, i. Age and the expected aneuploidy rate; ii. Ovarian biomarkers (i.e. antral follicle count [AFC] and anti-Müllerian hormone [AMH]), and iii. Ovarian response - provided a previous stimulation…

About 2,500 papers dated 2014–2016 were recovered by searching the PubMed database for Streptomyces, which are the richest known source of antibiotics. This review integrates around 100 of these papers in sections dealing with evolution, ecology, pathogenicity, growth and development, stress responses and secondary metabolism, gene expression, and technical advances. Genomic approaches have greatly accelerated progress. For example, it has been definitively shown that interspecies recombination of conserved genes has occurred during evolution, in addition to exchanges of some of the tens of thousands of non-conserved accessory genes. The closeness of the association of Streptomyces with plants, fungi, and insects has become clear and is reflected in the importance of regulators of cellulose and chitin utilisation in overall Streptomyces biology. Interestingly, endogenous cellulose-like glycans are also proving important in hyphal growth and in the clumping that affects industrial fermentations. Nucleotide secondary messengers, including cyclic di-GMP, have been shown to provide key…

The mammalian target of rapamycin, mTOR, plays key roles in cell growth and proliferation, acting at the catalytic subunit of two protein kinase complexes: mTOR complexes 1 and 2 (mTORC1/2). mTORC1 signaling is switched on by several oncogenic signaling pathways and is accordingly hyperactive in the majority of cancers. Inhibiting mTORC1 signaling has therefore attracted great attention as an anti-cancer therapy. However, progress in using inhibitors of mTOR signaling as therapeutic agents in oncology has been limited by a number of factors, including the fact that the classic mTOR inhibitor, rapamycin, inhibits only some of the effects of mTOR; the existence of several feedback loops; and the crucial importance of mTOR in normal physiology.

The ultimate aim of proteomics is to fully identify and quantify the entire complement of proteins and post-translational modifications in biological samples of interest. For the last 15 years, liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data-dependent acquisition (DDA) mode has been the standard for proteomics when sampling breadth and discovery were the main objectives; multiple reaction monitoring (MRM) LC-MS/MS has been the standard for targeted proteomics when precise quantification, reproducibility, and validation were the main objectives. Recently, improvements in mass spectrometer design and bioinformatics algorithms have resulted in the rediscovery and development of another sampling method: data-independent acquisition (DIA). DIA comprehensively and repeatedly samples every peptide in a protein digest, producing a complex set of mass spectra that is difficult to interpret without external spectral libraries. Currently, DIA approaches the identification breadth of DDA while achieving the reproducible quantification characteristic of MRM or its newest…

Metals play important roles in the human body, maintaining cell structure and regulating gene expression, neurotransmission, and antioxidant response, to name a few. However, excessive metal accumulation in the nervous system may be toxic, inducing oxidative stress, disrupting mitochondrial function, and impairing the activity of numerous enzymes. Damage caused by metal accumulation may result in permanent injuries, including severe neurological disorders. Epidemiological and clinical studies have shown a strong correlation between aberrant metal exposure and a number of neurological diseases, including Alzheimer's disease, amyotrophic lateral sclerosis, autism spectrum disorders, Guillain-Barré disease, Gulf War syndrome, Huntington's disease, multiple sclerosis, Parkinson's disease, and Wilson's disease. Here, we briefly survey the literature relating to the role of metals in neurodegeneration.

The growing cell wall in plants has conflicting requirements to be strong enough to withstand the high tensile forces generated by cell turgor pressure while selectively yielding to those forces to induce wall stress relaxation, leading to water uptake and polymer movements underlying cell wall expansion. In this article, I review emerging concepts of plant primary cell wall structure, the nature of wall extensibility and the action of expansins, family-9 and -12 endoglucanases, family-16 xyloglucan endotransglycosylase/hydrolase (XTH), and pectin methylesterases, and offer a critical assessment of their wall-loosening activity.

Single-cell RNA-sequencing methods are now robust and economically practical and are becoming a powerful tool for high-throughput, high-resolution transcriptomic analysis of cell states and dynamics. Single-cell approaches circumvent the averaging artifacts associated with traditional bulk population data, yielding new insights into the cellular diversity underlying superficially homogeneous populations. Thus far, single-cell RNA-sequencing has already shown great effectiveness in unraveling complex cell populations, reconstructing developmental trajectories, and modeling transcriptional dynamics. Ongoing technical improvements to single-cell RNA-sequencing throughput and sensitivity, the development of more sophisticated analytical frameworks for single-cell data, and an increasing array of complementary single-cell assays all promise to expand the usefulness and potential applications of single-cell transcriptomic profiling.

Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality and has an increasing incidence worldwide. HCC can be induced by multiple etiologies, is influenced by many risk factors, and has a complex pathogenesis. Furthermore, HCCs exhibit substantial heterogeneity, which compounds the difficulties in developing effective therapies against this highly lethal cancer. With advances in cancer biology and molecular and genetic profiling, a number of different mechanisms involved in the development and progression of HCC have been identified. Despite the advances in this area, the molecular pathogenesis of hepatocellular carcinoma is still not completely understood. This review aims to elaborate our current understanding of the most relevant genetic alterations and molecular pathways involved in the development and progression of HCC, and anticipate the potential impact of future advances on therapeutic drug development.

Biotechnology has almost unlimited potential to change our lives in very exciting ways. Many of the chemical reactions that produce these products can be fully optimized by performing them at extremes of temperature, pressure, salinity, and pH for efficient and cost-effective outcomes. Fortunately, there are many organisms (extremophiles) that thrive in extreme environments found in nature and offer an excellent source of replacement enzymes in lieu of mesophilic ones currently used in these processes. In this review, I discuss the current uses and some potential new applications of extremophiles and their products, including enzymes, in biotechnology.

In this article, we first present a summary of the general assumptions about Down syndrome (DS) still to be found in the literature. We go on to show how new research has modified these assumptions, pointing to a wide range of individual differences at every level of description. We argue that, in the context of significant increases in DS life expectancy, a focus on individual differences in trisomy 21 at all levels-genetic, cellular, neural, cognitive, behavioral, and environmental-constitutes one of the best approaches for understanding genotype/phenotype relations in DS and for exploring risk and protective factors for Alzheimer's disease in this high-risk population.

Sequencing reads overlapping polymorphic sites in diploid mammalian genomes may be assigned to one allele or the other. This holds the potential to detect gene expression, chromatin modifications, DNA methylation or nuclear interactions in an allele-specific fashion. SNPsplit is an allele-specific alignment sorter designed to read files in SAM/BAM format and determine the allelic origin of reads or read-pairs that cover known single nucleotide polymorphic (SNP) positions. For this to work libraries must have been aligned to a genome in which all known SNP positions were masked with the ambiguity base 'N' and aligned using a suitable mapping program such as Bowtie2, TopHat, STAR, HISAT2, HiCUP or Bismark. SNPsplit also provides an automated solution to generate N-masked reference genomes for hybrid mouse strains based on the variant call information provided by the Mouse Genomes Project. The unique ability of SNPsplit to work with various different kinds of sequencing data including RNA-Seq, ChIP-Seq, Bisulfite-Seq or Hi-C opens new avenues for the integrative exploration of…

Myasthenia gravis is an autoimmune disease of the neuromuscular junction (NMJ) caused by antibodies that attack components of the postsynaptic membrane, impair neuromuscular transmission, and lead to weakness and fatigue of skeletal muscle. This can be generalised or localised to certain muscle groups, and involvement of the bulbar and respiratory muscles can be life threatening. The pathogenesis of myasthenia gravis depends upon the target and isotype of the autoantibodies. Most cases are caused by immunoglobulin (Ig)G1 and IgG3 antibodies to the acetylcholine receptor (AChR). They produce complement-mediated damage and increase the rate of AChR turnover, both mechanisms causing loss of AChR from the postsynaptic membrane. The thymus gland is involved in many patients, and there are experimental and genetic approaches to understand the failure of immune tolerance to the AChR. In a proportion of those patients without AChR antibodies, antibodies to muscle-specific kinase (MuSK), or related proteins such as agrin and low-density lipoprotein receptor-related protein 4 (LRP4), are…

Central neural circuits orchestrate the behavioral and autonomic repertoire that maintains body temperature during environmental temperature challenges and alters body temperature during the inflammatory response and behavioral states and in response to declining energy homeostasis. This review summarizes the central nervous system circuit mechanisms controlling the principal thermoeffectors for body temperature regulation: cutaneous vasoconstriction regulating heat loss and shivering and brown adipose tissue for thermogenesis. The activation of these thermoeffectors is regulated by parallel but distinct efferent pathways within the central nervous system that share a common peripheral thermal sensory input. The model for the neural circuit mechanism underlying central thermoregulatory control provides a useful platform for further understanding of the functional organization of central thermoregulation, for elucidating the hypothalamic circuitry and neurotransmitters involved in body temperature regulation, and for the discovery of novel therapeutic approaches to modulating body…

There are many instances in genomics data analyses where measurements are made on a multivariate response. For example, alternative splicing can lead to multiple expressed isoforms from the same primary transcript. There are situations where differences (e.g. between normal and disease state) in the relative ratio of expressed isoforms may have significant phenotypic consequences or lead to prognostic capabilities. Similarly, knowledge of single nucleotide polymorphisms (SNPs) that affect splicing, so-called splicing quantitative trait loci (sQTL) will help to characterize the effects of genetic variation on gene expression. RNA sequencing (RNA-seq) has provided an attractive toolbox to carefully unravel alternative splicing outcomes and recently, fast and accurate methods for transcript quantification have become available. We propose a statistical framework based on the Dirichlet-multinomial distribution that can discover changes in isoform usage between conditions and SNPs that affect relative expression of transcripts using these quantifications. The Dirichlet-multinomial model…

This article summarizes existing work that indicates language maintenance and revitalization efforts result in health-related benefits for Native Americans and other indigenous populations. Although forced loss of ancestral language has been a feature of life in most indigenous communities since the first contact with Europeans, the pace of loss has accelerated in the past 50 years. Among the many hardships such communities face, an especially troubling one is lowered health status. There are indications, however, that language maintenance and revitalization efforts have positive effects on physical and communal health among indigenous populations. The types of language programs currently in place are outlined along with a variety of studies that will measure health improvement outcomes correlated with language revitalization efforts. Such evidence justifies increased support for language revitalization in order to improve health.

Household air pollution is a leading cause of disability-adjusted life years in Southeast Asia and the third leading cause of disability-adjusted life years globally. There are at least sixty sources of household air pollution, and these vary from country to country. Indoor tobacco smoking, construction material used in building houses, fuel used for cooking, heating and lighting, use of incense and various forms of mosquito repellents, use of pesticides and chemicals used for cleaning at home, and use of artificial fragrances are some of the various sources that contribute to household air pollution. Household air pollution affects all stages of life with multi-systemic health effects, and its effects are evident right from pre-conception to old age. In utero exposure to household air pollutants has been shown to have health effects which resonate over the entire lifetime. Exposures to indoor air pollutants in early childhood also tend to have repercussions throughout life. The respiratory system bears the maximum brunt, but effects on the cardiovascular system, endocrine system,…

In this short review, I will first summarize criteria by which environments can be considered "cold", with plant stature (size, height above ground) playing a central role for the climate actually experienced. Plants adapted to such environments have to cope with both extremes and with gradual influences of low temperature. The first requires freezing resistance, which is tightly coupled to developmental state (phenology) and prehistory (acclimation). Gradual low temperature constraints affect the growth process (meristems) long before they affect photosynthetic carbon gain. Hence, plants growing in cold climates are commonly not carbon limited.

Background Massive high-throughput sequencing of short, hypervariable segments of the 16S ribosomal RNA (rRNA) gene has transformed the methodological landscape describing microbial diversity within and across complex biomes. However, several studies have shown that the methodology rather than the biological variation is responsible for the observed sample composition and distribution. This compromises true meta-analyses, although this fact is often disregarded. Results To facilitate true meta-analysis of microbiome studies, we developed NG-Tax, a pipeline for 16S rRNA gene amplicon sequence analysis that was validated with different mock communities and benchmarked against QIIME as the currently most frequently used pipeline. The microbial composition of 49 independently amplified mock samples was characterized by sequencing two variable 16S rRNA gene regions, V4 and V5-V6, in three separate sequencing runs on Illumina’s HiSeq2000 platform. This allowed evaluating important factors of technical bias in taxonomic classification: 1) run-to-run sequencing variation, 2) PCR–error, and…

Orofacial clefts include cleft lip (CL), cleft palate (CP), and cleft lip and palate (CLP), which combined represent the largest group of craniofacial malformations in humans with an overall prevalence of one per 1,000 live births. Each of these birth defects shows strong familial aggregation, suggesting a major genetic component to their etiology. Genetic studies of orofacial clefts extend back centuries, but it has proven difficult to define any single etiologic mechanism because many genes appear to influence risk. Both linkage and association studies have identified several genes influencing risk, but these differ across families and across populations. Genome-wide association studies have identified almost two dozen different genes achieving genome-wide significance, and there are broad classes of 'causal genes' for orofacial clefts: a few genes strongly associated with risk and possibly directly responsible for Mendelian syndromes which include orofacial clefts as a key phenotypic feature of the syndrome, and multiple genes with modest individual effects on risk but capable of…

Overactivation of Wnt signaling is a hallmark of colorectal cancer (CRC). The Wnt pathway is a key regulator of both the early and the later, more invasive, stages of CRC development. In the normal intestine and colon, Wnt signaling controls the homeostasis of intestinal stem cells (ISCs) that fuel, via proliferation, upward movement of progeny cells from the crypt bottom toward the villus and differentiation into all cell types that constitute the intestine. Studies in recent years suggested that cancer stem cells (CSCs), similar to ISCs of the crypts, consist of a small subpopulation of the tumor and are responsible for the initiation and progression of the disease. Although various ISC signature genes were also identified as CRC markers and some of these genes were even demonstrated to have a direct functional role in CRC development, the origin of CSCs and their contribution to cancer progression is still debated. Here, we describe studies supporting a relationship between Wnt-regulated CSCs and the progression of CRC.

Bacterial infections cause 300 million cases of severe illness each year worldwide. Rapidly accelerating drug resistance further exacerbates this threat to human health. While dispersed (planktonic) bacteria represent a therapeutic challenge, bacterial biofilms present major hurdles for both diagnosis and treatment. Nanoparticles have emerged recently as tools for fighting drug-resistant planktonic bacteria and biofilms. In this review, we present the use of nanoparticles as active antimicrobial agents and drug delivery vehicles for antibacterial therapeutics. We further focus on how surface functionality of nanomaterials can be used to target both planktonic bacteria and biofilms.

IL-21 is a type I cytokine produced by T cells and natural killer T cells that has pleiotropic actions on a wide range of immune and non-immune cell types. Since its discovery in 2000, extensive studies on the biological actions of IL-21 have been performed in vitro and in vivo. Recent reports describing patients with primary immunodeficiency caused by mutations of IL21 or IL21R have further deepened our knowledge of the role of this cytokine in host defense. Elucidation of the molecular mechanisms that mediate IL-21's actions has provided the rationale for targeting IL-21 and IL-21 downstream mediators for therapeutic purposes. The use of next-generation sequencing technology has provided further insights into the complexity of IL-21 signaling and has identified transcription factors and co-factors involved in mediating the actions of this cytokine. In this review, we discuss recent advances in the biology and signaling of IL-21 and how this knowledge can be potentially translated into clinical settings.

Ongoing debates surrounding Open Access to the scholarly literature are multifaceted and complicated by disparate and often polarised viewpoints from engaged stakeholders. At the current stage, Open Access has become such a global issue that it is critical for all involved in scholarly publishing, including policymakers, publishers, research funders, governments, learned societies, librarians, and academic communities, to be well-informed on the history, benefits, and pitfalls of Open Access. In spite of this, there is a general lack of consensus regarding the advantages or disadvantages of Open Access at multiple levels. This review aims to to be a resource for current knowledge on the impacts of Open Access by synthesizing important research in three major areas of impact: academic, economic and societal. While there is clearly much scope for additional research, several key trends are identified, including a broad citation advantage for researchers who publish openly, as well as additional benefits to the non-academic dissemination of their work. The economic case for Open Access…

Podocytes are highly specialized cells of the kidney glomerulus that wrap around capillaries and that neighbor cells of the Bowman's capsule. When it comes to glomerular filtration, podocytes play an active role in preventing plasma proteins from entering the urinary ultrafiltrate by providing a barrier comprising filtration slits between foot processes, which in aggregate represent a dynamic network of cellular extensions. Foot processes interdigitate with foot processes from adjacent podocytes and form a network of narrow and rather uniform gaps. The fenestrated endothelial cells retain blood cells but permit passage of small solutes and an overlying basement membrane less permeable to macromolecules, in particular to albumin. The cytoskeletal dynamics and structural plasticity of podocytes as well as the signaling between each of these distinct layers are essential for an efficient glomerular filtration and thus for proper renal function. The genetic or acquired impairment of podocytes may lead to foot process effacement (podocyte fusion or retraction), a morphological hallmark…

Inflammasomes are high-molecular-weight protein complexes that are formed in the cytosolic compartment in response to danger- or pathogen-associated molecular patterns. These complexes enable activation of an inflammatory protease caspase-1, leading to a cell death process called pyroptosis and to proteolytic cleavage and release of pro-inflammatory cytokines interleukin (IL)-1β and IL-18. Along with caspase-1, inflammasome components include an adaptor protein, ASC, and a sensor protein, which triggers the inflammasome assembly in response to a danger signal. The inflammasome sensor proteins are pattern recognition receptors belonging either to the NOD-like receptor (NLR) or to the AIM2-like receptor family. While the molecular agonists that induce inflammasome formation by AIM2 and by several other NLRs have been identified, it is not well understood how the NLR family member NLRP3 is activated. Given that NLRP3 activation is relevant to a range of human pathological conditions, significant attempts are being made to elucidate the molecular mechanism of this process. In this…

Since its start in 1998, Software Carpentry has evolved from a week-long training course at the US national laboratories into a worldwide volunteer effort to improve researchers' computing skills. This paper explains what we have learned along the way, the challenges we now face, and our plans for the future.

Caloric restriction is the most effective and reproducible dietary intervention known to regulate aging and increase the healthy lifespan in various model organisms, ranging from the unicellular yeast to worms, flies, rodents, and primates. However, caloric restriction, which in most cases entails a 20-40% reduction of food consumption relative to normal intake, is a severe intervention that results in both beneficial and detrimental effects. Specific types of chronic, intermittent, or periodic dietary restrictions without chronic caloric restriction have instead the potential to provide a significant healthspan increase while minimizing adverse effects. Improved periodic or targeted dietary restriction regimens that uncouple the challenge of food deprivation from the beneficial effects will allow a safe intervention feasible for a major portion of the population. Here we focus on healthspan interventions that are not chronic or do not require calorie restriction.

The ability to easily and efficiently analyse RNA-sequencing data is a key strength of the Bioconductor project. Starting with counts summarised at the gene-level, a typical analysis involves pre-processing, exploratory data analysis, differential expression testing and pathway analysis with the results obtained informing future experiments and validation studies. In this workflow article, we analyse RNA-sequencing data from the mouse mammary gland, demonstrating use of the popular edgeR package to import, organise, filter and normalise the data, followed by the limma package with its voom method, linear modelling and empirical Bayes moderation to assess differential expression and perform gene set testing. This pipeline is further enhanced by the Glimma package which enables interactive exploration of the results so that individual samples and genes can be examined by the user. The complete analysis offered by these three packages highlights the ease with which researchers can turn the raw counts from an RNA-sequencing experiment into biological insights using Bioconductor.

Traumatic spinal cord injuries (SCIs) affect 1.3 million North Americans, producing devastating physical, social, and vocational impairment. Pathophysiologically, the initial mechanical trauma is followed by a significant secondary injury which includes local ischemia, pro-apoptotic signaling, release of cytotoxic factors, and inflammatory cell infiltration. Expedient delivery of medical and surgical care during this critical period can improve long-term functional outcomes, engendering the concept of "Time is Spine". We emphasize the importance of expeditious care while outlining the initial clinical and radiographic assessment of patients. Key evidence-based early interventions (surgical decompression, blood pressure augmentation, and methylprednisolone) are also reviewed, including findings of the landmark Surgical Timing in Acute Spinal Cord Injury Study (STASCIS). We then describe other neuroprotective approaches on the edge of translation such as the sodium-channel blocker riluzole, the anti-inflammatory minocycline, and therapeutic hypothermia. We also review promising…

Sequencing reads overlapping polymorphic sites in diploid mammalian genomes may be assigned to one allele or the other. This holds the potential to detect gene expression, chromatin modifications, DNA methylation or nuclear interactions in an allele-specific fashion. SNPsplit is an allele-specific alignment sorter designed to read files in SAM/BAM format and determine the allelic origin of reads or read-pairs that cover known single nucleotide polymorphic (SNP) positions. For this to work libraries must have been aligned to a genome in which all known SNP positions were masked with the ambiguity base 'N' and aligned using a suitable mapping program such as Bowtie2, TopHat, STAR, HISAT2, HiCUP or Bismark. SNPsplit also provides an automated solution to generate N-masked reference genomes for hybrid mouse strains based on the variant call information provided by the Mouse Genomes Project. The unique ability of SNPsplit to work with various different kinds of sequencing data including RNA-Seq, ChIP-Seq, Bisulfite-Seq or Hi-C opens new avenues for the integrative exploration of…