The incidence of preterm birth exceeds 10% worldwide. There are significant disparities in the frequency of preterm birth among populations within countries, and women of African ancestry disproportionately bear the burden of risk in the United States. In the present study, we report a community resource that includes ‘omics’ data from approximately 12,000 samples as part of the integrative Human Microbiome Project. Longitudinal analyses of 16S ribosomal RNA, metagenomic, metatranscriptomic and cytokine profiles from 45 preterm and 90 term birth controls identified harbingers of preterm birth in this cohort of women predominantly of African ancestry. Women who delivered preterm exhibited significantly lower vaginal levels of Lactobacillus crispatus and higher levels of BVAB1, Sneathia amnii, TM7-H1, a group of Prevotella species and nine additional taxa. The first representative genomes of BVAB1 and TM7-H1 are described. Preterm-birth-associated taxa were correlated with proinflammatory cytokines in vaginal fluid. These findings highlight new opportunities for assessment of the risk of preterm birth.

Genomes of animals as different as sponges and humans show conservation of global architecture. Here we show that multiple genomic features including transposon diversity, developmental gene repertoire, physical gene order, and intron-exon organization are shattered in the tunicate Oikopleura, belonging to the sister group of vertebrates and retaining chordate morphology. Ancestral architecture of animal genomes can be deeply modified and may therefore be largely nonadaptive. This rapidly evolving animal lineage thus offers unique perspectives on the level of genome plasticity. It also illuminates issues as fundamental as the mechanisms of intron gain.

We compiled a data set of 541 bankfull measurements of alluvial rivers (see supporting information) and used Bayesian linear regression to examine empirical and theoretical support for the hypothesis that alluvial channels adjust to a predictable condition of basal shear stress as a function of sediment transport mode. An empirical closure based on channel slope, bankfull channel depth, and median grain size is proposed and results in the scaling of bankfull Shields stress with the inverse square root of particle Reynolds number. The empirical relationship is sufficient for purposes of quantifying paleohydraulic conditions in ancient alluvial channels. However, it is not currently appropriate for application to alluvial channels on extraterrestrial bodies because it depends on constant-valued, Earth-based coefficients.

A crude oil and a synthetic reservoir water are used to prepare water-in-oil emulsions. The droplet-size distribution of water-in-oil emulsions is measured by digitally processing optical micrographs. The time evolution of the droplet-size distribution is used as a proxy of emulsion stability. A procedure for obtaining homogeneous aliquots of the initial emulsion is developed. The procedure yields statistical replicas of the initial sample that allow one to measure size distributions through direct observation of optical micrographs for a period of time of up to 7 days. The synthetic reservoir water is diluted by the addition of distilled water to determine how the water ionic strength affected emulsion stability. A detailed dropletsize distribution analysis supports the log-hyperbolic distribution as a better fit to the experimental observations than the Weibull or log-normal distributions. The inferred qualitative rates of coalescence indicate that emulsions are more stable at lower ionic strength of the aqueous phase. This result is consistent with previous emulsion characterization using electrorheology and bottle tests, demonstrating the importance of often overlooked aqueous-phase composition.

Despite the widespread use of self-rated health (SRH) in population health studies, the meaning of this holistic health judgment remains an open question. Gender differences in health, an issue of utmost importance in population research and policy, are often measured with SRH; the comparisons could be biased if men and women differ in how they form their health judgment. The aim of this study is to examine whether men and women differ in how health inputs predict their health rating across the adult life span. We use the 2002–2015 National Health Interview Survey data from US-born respondents aged 25–84. Ordered logistic models of SRH as a function of 24 health measures including medical conditions and symptoms, mental health, functioning, health care utilization, and health behaviors, all interacted with gender, test how the measures influence health ratings and the extent to which these influences differ by gender. Using a Bayesian approach, we then compare how closely a select health measure (K6 score) corresponds to SRH levels among men and women. We find little systematic gender difference in the structure of SRH: men and women use wide-ranging health-related frames of reference in a similar way when making health judgments, with some exceptions: mid-life and older men weigh physical functioning deficits and negative health behaviors more heavily than women. Women report worse SRH than men on average but this only holds through mid-adulthood and is reversed at older ages; moreover, the gross female disadvantage disappears when differences in socio-economic and health covariates are considered. Our findings suggest that the meaning of SRH is similar for women and men. Both groups use a broad range of health-related information in forming their health judgment. This conclusion strengthens the validity of SRH in measuring gender differences in health.

Conserving a declining species that is facing many threats, including overlap of its habitats with energy extraction activities, depends upon identifying and prioritizing the value of the habitats that remain. In addition, habitat quality is often compromised when source habitats are lost or fragmented due to anthropogenic development. Our objective was to build an ecological model to classify and map habitat quality in terms of source or sink dynamics for Greater Sage-Grouse (Centrocercus urophasianus) in the Atlantic Rim Project Area (ARPA), a developing coalbed natural gas field in south-central Wyoming, USA. We used occurrence and survival modeling to evaluate relationships between environmental and anthropogenic variables at multiple spatial scales and for all female summer life stages, including nesting, brood-rearing, and non-brooding females. For each life stage, we created resource selection functions (RSFs). We weighted the RSFs and combined them to form a female summer occurrence map. We modeled survival also as a function of spatial variables for nest, brood, and adult female summer survival. Our survival-models were mapped as survival probability functions individually and then combined with fixed vital rates in a fitness metric model that, when mapped, predicted habitat productivity (productivity map). Our results demonstrate a suite of environmental and anthropogenic variables at multiple scales that were predictive of occurrence and survival. We created a source-sink map by overlaying our female summer occurrence map and productivity map to predict habitats contributing to population surpluses (source habitats) or deficits (sink habitat) and low-occurrence habitats on the landscape. The source-sink map predicted that of the Sage-Grouse habitat within the ARPA, 30% was primary source, 29% was secondary source, 4% was primary sink, 6% was secondary sink, and 31% was low occurrence. Our results provide evidence that energy development and avoidance of energy infrastructure were probably reducing the amount of source habitat within the ARPA landscape. Our source-sink map provides managers with a means of prioritizing habitats for conservation planning based on source and sink dynamics. The spatial identification of high value (i.e., primary source) as well as suboptimal (i.e., primary sink) habitats allows for informed energy development to minimize effects on local wildlife populations.

Background: Recent studies of various human microbiome habitats have revealed thousands of bacterial species and the existence of large variation in communities of microorganisms in the same habitats across individual human subjects. Previous efforts to summarize this diversity, notably in the human gut and vagina, have categorized microbiome profiles by clustering them into community state types (CSTs). The functional relevance of specific CSTs has not been established. Objective: We investigate whether CSTs can be used to assess dynamics in the microbiome. Design: We conduct a re-analysis of five sequencing-based microbiome surveys derived from vaginal samples with repeated measures. Results: We observe that detection of a CST transition is largely insensitive to choices in methods for normalization or clustering. We find that healthy subjects persist in a CST for two to three weeks or more on average, while those with evidence of dysbiosis tend to change more often. Changes in CST can be gradual or occur over less than one day. Upcoming CST changes and switches to high-risk CSTs can be predicted with high accuracy in certain scenarios. Finally, we observe that presence of Gardnerella vaginalis is a strong predictor of an upcoming CST change. Conclusion: Overall, our results show that the CST concept is useful for studying microbiome dynamics.

We systematically compare an event-by-event heavy-ion collision model to data from the Large Hadron Collider. Using a general Bayesian method, we probe multiple model parameters including fundamental quark-gluon plasma properties such as the specific shear viscosity η/s, calibrate the model to optimally reproduce experimental data, and extract quantitative constraints for all parameters simultaneously. The method is universal and easily extensible to other data and collision models.