Collisional N-Body Dynamics Coupled to Self-Gravitating Magnetohydrodynamics Reveals Dynamical Binary Formation

We describe a star cluster formation model that includes individual star formation from self-gravitating, magnetized gas, coupled to collisional stellar dynamics. The model uses the Astrophysical Multi-purpose Software Environment (AMUSE) to integrate an adaptive-mesh magnetohydrodynamics code (FLASH) with a fourth order Hermite N-body code (ph4), a stellar evolution code (SeBa), and a method for resolving binary evolution (multiples). This combination yields unique star formation simulations that allow us to study binaries formed dynamically from interactions with both other stars and dense, magnetized gas subject to stellar feedback during the birth and early evolution of stellar clusters. We find that for massive stars, our simulations are consistent with the observed dynamical binary fractions and mass ratios. However, our binary fraction drops well below observed values for lower mass stars, presumably due to unincluded binary formation during initial star formation. Further, we observe a build up of binaries near the hard-soft boundary that may be an important mechanism driving early cluster contraction.Comment: 14 pages, 12 figures. Submitted to Ap

Modelling of the Effects of Stellar Feedback during Star Cluster Formation Using a Hybrid Gas and N-Body Method

Understanding the formation of stellar clusters requires following the interplay between gas and newly formed stars accurately. We therefore couple the magnetohydrodynamics code FLASH to the N-body code ph4 and the stellar evolution code SeBa using the Astrophysical Multipurpose Software Environment (AMUSE) to model stellar dynamics, evolution, and collisional N-body dynamics and the formation of binary and higher-order multiple systems, while implementing stellar feedback in the form of radiation, stellar winds and supernovae in FLASH. We here describe the algorithms used for each of these processes. We denote this integrated package Torch. We then use this novel numerical method to simulate the formation and early evolution of several examples of open clusters of ~1000 stars formed from clouds with a mass range of 10^3-10^5 M_sun. Analyzing the effects of stellar feedback on the gas and stars of the natal clusters, we find that in these examples, the stellar clusters are resilient to disruption, even in the presence of intense feedback. This can even slightly increase the amount of dense, Jeans unstable gas by sweeping up shells; thus, a stellar wind strong enough to trap its own H II region shows modest triggering of star formation. Our clusters are born moderately mass segregated, an effect enhanced by feedback, and retained after the ejection of their natal gas, in agreement with observations.Comment: Accepted to ApJ. 29 pages, 18 figures. Source code at https://bitbucket.org/torch-sf/torch/ and documentation at https://torch-sf.bitbucket.io

Implementing Primordial Binaries in Simulations of Star Cluster Formation with a Hybrid MHD and Direct N-Body Method

The fraction of stars in binary systems within star clusters is important for their evolution, but what proportion of binaries form by dynamical processes after initial stellar accretion remains unknown. In previous work, we showed that dynamical interactions alone produced too few low-mass binaries compared to observations. We therefore implement an initial population of binaries in the coupled MHD and direct N-body star cluster formation code Torch. We compare simulations with, and without, initial binary populations and follow the dynamical evolution of the binary population in both sets of simulations, finding that both dynamical formation and destruction of binaries take place. Even in the first few million years of star formation, we find that an initial population of binaries is needed at all masses to reproduce observed binary fractions for binaries with mass ratios above the $q \geq 0.1$ detection limit. Our simulations also indicate that dynamical interactions in the presence of gas during cluster formation modify the initial distributions towards binaries with smaller primary masses, larger mass ratios, smaller semi-major axes and larger eccentricities. Systems formed dynamically do not have the same properties as the initial systems, and systems formed dynamically in the presence of an initial population of binaries differ from those formed in simulations with single stars only. Dynamical interactions during the earliest stages of star cluster formation are important for determining the properties of binary star systems.Comment: 15 pages, 14 figures, submitted to MNRAS and edited to address positive referee's repor

Antifungal drug resistance evoked via RNAi-dependent epimutations

Microorganisms evolve via mechanisms spanning sexual/parasexual reproduction, mutators, aneuploidy, Hsp90, and even prions. Mechanisms that may seem detrimental can be repurposed to generate diversity. Here we show the human fungal pathogen Mucor circinelloides develops spontaneous resistance to the antifungal drug FK506 (tacrolimus) via two distinct mechanisms. One involves Mendelian mutations that confer stable drug resistance; the other occurs via an epigenetic RNA interference (RNAi)-mediated pathway resulting in unstable drug resistance. The peptidyl-prolyl isomerase FKBP12 interacts with FK506 forming a complex that inhibits the protein phosphatase calcineurin1. Calcineurin inhibition by FK506 blocks M. circinelloides transition to hyphae and enforces yeast growth2. Mutations in the fkbA gene encoding FKBP12 or the calcineurin cnbR or cnaA genes confer FK506 resistance (FK506R) and restore hyphal growth. In parallel, RNAi is spontaneously triggered to silence the FKBP12 fkbA gene, giving rise to drug-resistant epimutants. FK506R epimutants readily reverted to the drug-sensitive wild-type (WT) phenotype when grown without drug. The establishment of these epimutants is accompanied by generation of abundant fkbA small RNA (sRNA) and requires the RNAi pathway as well as other factors that constrain or reverse the epimutant state. Silencing involves generation of a double-stranded RNA (dsRNA) trigger intermediate from the fkbA mature mRNA to produce antisense fkbA RNA. This study uncovers a novel epigenetic RNAi-based epimutation mechanism controlling phenotypic plasticity, with possible implications for antimicrobial drug resistance and RNAi-regulatory mechanisms in fungi and other eukaryotes

Count every newborn; a measurement improvement roadmap for coverage data.

BACKGROUND: The Every Newborn Action Plan (ENAP), launched in 2014, aims to end preventable newborn deaths and stillbirths, with national targets of ≤12 neonatal deaths per 1000 live births and ≤12 stillbirths per 1000 total births by 2030. This requires ambitious improvement of the data on care at birth and of small and sick newborns, particularly to track coverage, quality and equity. METHODS: In a multistage process, a matrix of 70 indicators were assessed by the Every Newborn steering group. Indicators were graded based on their availability and importance to ENAP, resulting in 10 core and 10 additional indicators. A consultation process was undertaken to assess the status of each ENAP core indicator definition, data availability and measurement feasibility. Coverage indicators for the specific ENAP treatment interventions were assigned task teams and given priority as they were identified as requiring the most technical work. Consultations were held throughout. RESULTS: ENAP published 10 core indicators plus 10 additional indicators. Three core impact indicators (neonatal mortality rate, maternal mortality ratio, stillbirth rate) are well defined, with future efforts needed to focus on improving data quantity and quality. Three core indicators on coverage of care for all mothers and newborns (intrapartum/skilled birth attendance, early postnatal care, essential newborn care) have defined contact points, but gaps exist in measuring content and quality of the interventions. Four core (antenatal corticosteroids, neonatal resuscitation, treatment of serious neonatal infections, kangaroo mother care) and one additional coverage indicator for newborns at risk or with complications (chlorhexidine cord cleansing) lack indicator definitions or data, especially for denominators (population in need). To address these gaps, feasible coverage indicator definitions are presented for validity testing. Measurable process indicators to help monitor health service readiness are also presented. A major measurement gap exists to monitor care of small and sick babies, yet signal functions could be tracked similarly to emergency obstetric care. CONCLUSIONS: The ENAP Measurement Improvement Roadmap (2015-2020) outlines tools to be developed (e.g., improved birth and death registration, audit, and minimum perinatal dataset) and actions to test, validate and institutionalise proposed coverage indicators. The roadmap presents a unique opportunity to strengthen routine health information systems, crosslinking these data with civil registration and vital statistics and population-based surveys. Real measurement change requires intentional transfer of leadership to countries with the greatest disease burden and will be achieved by working with centres of excellence and existing networks

De novo characterization of the gametophyte transcriptome in bracken fern, Pteridium aquilinum

<p>Abstract</p> <p>Background</p> <p>Because of their phylogenetic position and unique characteristics of their biology and life cycle, ferns represent an important lineage for studying the evolution of land plants. Large and complex genomes in ferns combined with the absence of economically important species have been a barrier to the development of genomic resources. However, high throughput sequencing technologies are now being widely applied to non-model species. We leveraged the Roche 454 GS-FLX Titanium pyrosequencing platform in sequencing the gametophyte transcriptome of bracken fern (<it>Pteridium aquilinum</it>) to develop genomic resources for evolutionary studies.</p> <p>Results</p> <p>681,722 quality and adapter trimmed reads totaling 254 Mbp were assembled <it>de novo </it>into 56,256 unique sequences (i.e. unigenes) with a mean length of 547.2 bp and a total assembly size of 30.8 Mbp with an average read-depth coverage of 7.0×. We estimate that 87% of the complete transcriptome has been sequenced and that all transcripts have been tagged. 61.8% of the unigenes had blastx hits in the NCBI nr protein database, representing 22,596 unique best hits. The longest open reading frame in 52.2% of the unigenes had positive domain matches in InterProScan searches. We assigned 46.2% of the unigenes with a GO functional annotation and 16.0% with an enzyme code annotation. Enzyme codes were used to retrieve and color KEGG pathway maps. A comparative genomics approach revealed a substantial proportion of genes expressed in bracken gametophytes to be shared across the genomes of <it>Arabidopsis</it>, <it>Selaginella </it>and <it>Physcomitrella</it>, and identified a substantial number of potentially novel fern genes. By comparing the list of <it>Arabidopsis </it>genes identified by blast with a list of gametophyte-specific <it>Arabidopsis </it>genes taken from the literature, we identified a set of potentially conserved gametophyte specific genes. We screened unigenes for repetitive sequences to identify 548 potentially-amplifiable simple sequence repeat loci and 689 expressed transposable elements.</p> <p>Conclusions</p> <p>This study is the first comprehensive transcriptome analysis for a fern and represents an important scientific resource for comparative evolutionary and functional genomics studies in land plants. We demonstrate the utility of high-throughput sequencing of a normalized cDNA library for <it>de novo </it>transcriptome characterization and gene discovery in a non-model plant.</p

The time scale of recombination rate evolution in great apes

We present three linkage-disequilibrium (LD)-based recombination maps generated using whole-genome sequence data from 10 Nigerian chimpanzees, 13 bonobos, and 15 western gorillas, collected as part of the Great Ape Genome Project (Prado-Martinez J, et al. 2013. Great ape genetic diversity and population history. Nature 499:471-475). We also identified species-specific recombination hotspots in each group using a modified LDhot framework, which greatly improves statistical power to detect hotspots at varying strengths. We show that fewer hotspots are shared among chimpanzee subspecies than within human populations, further narrowing the time scale of complete hotspot turnover. Further, using species-specific PRDM9 sequences to predict potential binding sites (PBS), we show higher predicted PRDM9 binding in recombination hotspots as compared to matched cold spot regions in multiple great ape species, including at least one chimpanzee subspecies. We found that correlations between broad-scale recombination rates decline more rapidly than nucleotide divergence between species. We also compared the skew of recombination rates at centromeres and telomeres between species and show a skew from chromosome means extending as far as 10-15Mb from chromosome ends. Further, we examined broad-scale recombination rate changes near a translocation in gorillas and found minimal differences as compared to other great ape species perhaps because the coordinates relative to the chromosome ends were unaffected. Finally, on the basis of multiple linear regression analysis, we found that various correlates of recombination rate persist throughout the African great apes including repeats, diversity, and divergence. Our study is the first to analyze within- And between-species genome-wide recombination rate variation in several close relatives

Structure and Age Jointly Influence Rates of Protein Evolution

What factors determine a protein's rate of evolution are actively debated. Especially unclear is the relative role of intrinsic factors of present-day proteins versus historical factors such as protein age. Here we study the interplay of structural properties and evolutionary age, as determinants of protein evolutionary rate. We use a large set of one-to-one orthologs between human and mouse proteins, with mapped PDB structures. We report that previously observed structural correlations also hold within each age group – including relationships between solvent accessibility, designabililty, and evolutionary rates. However, age also plays a crucial role: age modulates the relationship between solvent accessibility and rate. Additionally, younger proteins, despite being less designable, tend to evolve faster than older proteins. We show that previously reported relationships between age and rate cannot be explained by structural biases among age groups. Finally, we introduce a knowledge-based potential function to study the stability of proteins through large-scale computation. We find that older proteins are more stable for their native structure, and more robust to mutations, than younger ones. Our results underscore that several determinants, both intrinsic and historical, can interact to determine rates of protein evolution

Setting research priorities to improve global newborn health and prevent stillbirths by 2025.

BACKGROUND: In 2013, an estimated 2.8 million newborns died and 2.7 million were stillborn. A much greater number suffer from long term impairment associated with preterm birth, intrauterine growth restriction, congenital anomalies, and perinatal or infectious causes. With the approaching deadline for the achievement of the Millennium Development Goals (MDGs) in 2015, there was a need to set the new research priorities on newborns and stillbirth with a focus not only on survival but also on health, growth and development. We therefore carried out a systematic exercise to set newborn health research priorities for 2013-2025. METHODS: We used adapted Child Health and Nutrition Research Initiative (CHNRI) methods for this prioritization exercise. We identified and approached the 200 most productive researchers and 400 program experts, and 132 of them submitted research questions online. These were collated into a set of 205 research questions, sent for scoring to the 600 identified experts, and were assessed and scored by 91 experts. RESULTS: Nine out of top ten identified priorities were in the domain of research on improving delivery of known interventions, with simplified neonatal resuscitation program and clinical algorithms and improved skills of community health workers leading the list. The top 10 priorities in the domain of development were led by ideas on improved Kangaroo Mother Care at community level, how to improve the accuracy of diagnosis by community health workers, and perinatal audits. The 10 leading priorities for discovery research focused on stable surfactant with novel modes of administration for preterm babies, ability to diagnose fetal distress and novel tocolytic agents to delay or stop preterm labour. CONCLUSION: These findings will assist both donors and researchers in supporting and conducting research to close the knowledge gaps for reducing neonatal mortality, morbidity and long term impairment. WHO, SNL and other partners will work to generate interest among key national stakeholders, governments, NGOs, and research institutes in these priorities, while encouraging research funders to support them. We will track research funding, relevant requests for proposals and trial registers to monitor if the priorities identified by this exercise are being addressed