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Improving the reproducibility of biomedical research is a major challenge. Transparent and accurate reporting is vital to this process; it allows readers to assess the reliability of the findings and repeat or build upon the work of other researchers. The ARRIVE guidelines (Animal Research: Reporting In Vivo Experiments) were developed in 2010 to help authors and journals identify the minimum information necessary to report in publications describing in vivo experiments. Despite widespread endorsement by the scientific community, the impact of ARRIVE on the transparency of reporting in animal research publications has been limited. We have revised the ARRIVE guidelines to update them and facilitate their use in practice. The revised guidelines are published alongside this paper. This explanation and elaboration document was developed as part of the revision. It provides further information about each of the 21 items in ARRIVE 2.0, including the rationale and supporting evidence for their inclusion in the guidelines, elaboration of details to report, and examples of good reporting from the published literature. This document also covers advice and best practice in the design and conduct of animal studies to support researchers in improving standards from the start of the experimental design process through to publication.

\"Attempts to distinguish a science of life at the turn of the nineteenth century faced a number of challenges. A central difficulty was clearly demarcating the living from the nonliving experimentally and conceptually. The more closely the boundaries between organic and inorganic phenomena were examined, the more they expanded and thwarted any clear delineation. Experimenting at the Boundaries of Life traces the debates surrounding the first articulations of a science of life in a variety of texts and practices centered on German contexts. Joan Steigerwald examines the experiments on the processes of organic vitality, such as excitability and generation, undertaken across the fields of natural history, physiology, physics and chemistry. She highlights the sophisticated reflections on the problem of experimenting on living beings by investigators, and relates these epistemic concerns directly to the philosophies of nature of Kant and Schelling. Her book skillfully ties these epistemic reflections to arguments by the Romantic writers Novalis and Goethe for the aesthetic aspects of inquiries into the living world and the figurative languages in which understandings of nature were expressed\"-- Provided by publisher.

OpenMM is a molecular dynamics simulation toolkit with a unique focus on extensibility. It allows users to easily add new features, including forces with novel functional forms, new integration algorithms, and new simulation protocols. Those features automatically work on all supported hardware types (including both CPUs and GPUs) and perform well on all of them. In many cases they require minimal coding, just a mathematical description of the desired function. They also require no modification to OpenMM itself and can be distributed independently of OpenMM. This makes it an ideal tool for researchers developing new simulation methods, and also allows those new methods to be immediately available to the larger community.

\"Combining the best current medical knowledge with a new approach grounded in integrative medicine, Chopra and Tanzi offer a groundbreaking new model of healing and the healing system, one of the main mysteries in the mind-body connection\"-- Provided by publisher.

Big, time-scaled phylogenies are fundamental to connecting evolutionary processes to modern biodiversity patterns. Yet inferring reliable phylogenetic trees for thousands of species involves numerous trade-offs that have limited their utility to comparative biologists. To establish a robust evolutionary timescale for all approximately 6,000 living species of mammals, we developed credible sets of trees that capture root-to-tip uncertainty in topology and divergence times. Our \"backbone-and-patch\" approach to tree building applies a newly assembled 31-gene supermatrix to two levels of Bayesian inference: (1) backbone relationships and ages among major lineages, using fossil node or tip dating, and (2) species-level \"patch\" phylogenies with nonoverlapping in-groups that each correspond to one representative lineage in the backbone. Species unsampled for DNA are either excluded (\"DNA-only\" trees) or imputed within taxonomic constraints using branch lengths drawn from local birth-death models (\"completed\" trees). Joining time-scaled patches to backbones results in species-level trees of extant Mammalia with all branches estimated under the same modeling framework, thereby facilitating rate comparisons among lineages as disparate as marsupials and placentals. We compare our phylogenetic trees to previous estimates of mammal-wide phylogeny and divergence times, finding that (1) node ages are broadly concordant among studies, and (2) recent (tip-level) rates of speciation are estimated more accurately in our study than in previous \"supertree\" approaches, in which unresolved nodes led to branch-length artifacts. Credible sets of mammalian phylogenetic history are now available for download at http://vertlife.org/phylosubsets, enabling investigations of long-standing questions in comparative biology.

\"This book is the first history of the science of human genetics in the Middle East, from its roots in colonial anthropology and medicine to present-day genomic projects. Genetic Nationalism reveals the effects of international genetic discourses on Middle Eastern nationalisms and the significance of Middle Eastern genetics to the international scientific community. This book illuminates how genetic research simultaneously promotes national interests in the global community and enforces colonialism at home. Elise Burton reveals the political, social, and technological processes that have shaped genetic research in the twentieth century, tracing the global incorporation of nationalist historical narratives and identities into the broader understanding of human evolution\"-- Provided by publisher.

The availability of highly susceptible HIV target cells that can rapidly reach the mucosal lymphoid tissues may increase the chances of an otherwise rare transmission event to occur. Expression of α 4 β 7 is required for trafficking of immune cells to gut inductive sites where HIV can expand and it is expressed at high level on cells particularly susceptible to HIV infection. We hypothesized that HSV-2 modulates the expression of α 4 β 7 and other homing receptors in the vaginal tissue and that this correlates with the increased risk of HIV acquisition in HSV-2 positive individuals. To test this hypothesis we used an in vivo rhesus macaque (RM) model of HSV-2 vaginal infection and a new ex vivo model of macaque vaginal explants. In vivo we found that HSV-2 latently infected RMs appeared to be more susceptible to vaginal SHIV SF162P3 infection, had higher frequency of α 4 β 7 high CD4 + T cells in the vaginal tissue and higher expression of α 4 β 7 and CD11c on vaginal DCs. Similarly, ex vivo HSV-2 infection increased the susceptibility of the vaginal tissue to SHIV SF162P3 . HSV-2 infection increased the frequencies of α 4 β 7 high CD4 + T cells and this directly correlated with HSV-2 replication. A higher amount of inflammatory cytokines in vaginal fluids of the HSV-2 infected animals was similar to those found in the supernatants of the infected explants. Remarkably, the HSV-2-driven increase in the frequency of α 4 β 7 high CD4 + T cells directly correlated with SHIV replication in the HSV-2 infected tissues. Our results suggest that the HSV-2-driven increase in availability of CD4 + T cells and DCs that express high levels of α 4 β 7 is associated with the increase in susceptibility to SHIV due to HSV-2. This may persists in absence of HSV-2 shedding. Hence, higher availability of α 4 β 7 positive HIV target cells in the vaginal tissue may constitute a risk factor for HIV transmission. Understanding the factors that correlate with an increased risk of acquiring HIV infection is key to identify new means of preventing HIV transmission. HSV-2 infection increases the risk of HIV transmission even in absence of visible lesions and inflammation. In order to explore HSV-2− associated factors that could explain this phenomenon, we used a model of asymptomatic HSV-2 infection in macaques and ex vivo cultures of biopsied vaginal tissue. We determined that HSV-2 infection is associated with an increase in subsets of immune cells that express high levels of α 4 β 7 , a molecule needed by the cells to reach the gut and the gut lymphoid tissues. The gut is an important site for HIV infection and pathogenesis and CD4 + T cells expressing high levels of α 4 β 7 (α 4 β 7 high ) are highly susceptible to the virus. We determined that the HSV-2-driven increase in these cells correlates with an increased susceptibility of the vaginal mucosa to SIV infection. Thus, our results suggest that an increased availability of α 4 β 7 high cells at the mucosal site of HIV exposure may constitute a risk factor for HIV acquisition in HSV-2 positive and, possibly, negative individuals.

The advent of high throughput technologies has led to a wealth of publicly available 'omics data coming from different sources, such as transcriptomics, proteomics, metabolomics. Combining such large-scale biological data sets can lead to the discovery of important biological insights, provided that relevant information can be extracted in a holistic manner. Current statistical approaches have been focusing on identifying small subsets of molecules (a 'molecular signature') to explain or predict biological conditions, but mainly for a single type of 'omics. In addition, commonly used methods are univariate and consider each biological feature independently. We introduce mixOmics, an R package dedicated to the multivariate analysis of biological data sets with a specific focus on data exploration, dimension reduction and visualisation. By adopting a systems biology approach, the toolkit provides a wide range of methods that statistically integrate several data sets at once to probe relationships between heterogeneous 'omics data sets. Our recent methods extend Projection to Latent Structure (PLS) models for discriminant analysis, for data integration across multiple 'omics data or across independent studies, and for the identification of molecular signatures. We illustrate our latest mixOmics integrative frameworks for the multivariate analyses of 'omics data available from the package.

Bacterial communities associated with roots impact the health and nutrition of the host plant. The dynamics of these microbial assemblies over the plant life cycle are, however, not well understood. Here, we use dense temporal sampling of 1,510 samples from root spatial compartments to characterize the bacterial and archaeal components of the root-associated microbiota of field grown rice (Oryza sativa) over the course of 3 consecutive growing seasons, as well as 2 sites in diverse geographic regions. The root microbiota was found to be highly dynamic during the vegetative phase of plant growth and then stabilized compositionally for the remainder of the life cycle. Bacterial and archaeal taxa conserved between field sites were defined as predictive features of rice plant age by modeling using a random forest approach. The age-prediction models revealed that drought-stressed plants have developmentally immature microbiota compared to unstressed plants. Further, by using genotypes with varying developmental rates, we show that shifts in the microbiome are correlated with rates of developmental transitions rather than age alone, such that different microbiota compositions reflect juvenile and adult life stages. These results suggest a model for successional dynamics of the root-associated microbiota over the plant life cycle.