The environment power system analysis tool development program

The Environment Power System Analysis Tool (EPSAT) is being developed to provide space power system design engineers with an analysis tool for determining system performance of power systems in both naturally occurring and self-induced environments. The program is producing an easy to use computer aided engineering (CAE) tool general enough to provide a vehicle for technology transfer from space scientists and engineers to power system design engineers. The results of the project after two years of a three year development program are given. The EPSAT approach separates the CAE tool into three distinct functional units: a modern user interface to present information, a data dictionary interpreter to coordinate analysis; and a data base for storing system designs and results of analysis

Aerial dissemination of Clostridium difficile spores

Background: Clostridium difficile-associated diarrhoea (CDAD) is a frequently occurring healthcare-associated infection, which is responsible for significant morbidity and mortality amongst elderly patients in healthcare facilities. Environmental contamination is known to play an important contributory role in the spread of CDAD and it is suspected that contamination might be occurring as a result of aerial dissemination of C. difficile spores. However previous studies have failed to isolate C. difficile from air in hospitals. In an attempt to clarify this issue we undertook a short controlled pilot study in an elderly care ward with the aim of culturing C. difficile from the air. Methods: In a survey undertaken during February (two days) 2006 and March (two days) 2007, air samples were collected using a portable cyclone sampler and surface samples collected using contact plates in a UK hospital. Sampling took place in a six bedded elderly care bay (Study) during February 2006 and in March 2007 both the study bay and a four bedded orthopaedic bay (Control). Particulate material from the air was collected in Ringer's solution, alcohol shocked and plated out in triplicate onto Brazier's CCEY agar without egg yolk, but supplemented with 5 mg/L of lysozyme. After incubation, the identity of isolates was confirmed by standard techniques. Ribotyping and REP-PCR fingerprinting were used to further characterise isolates. Results: On both days in February 2006, C. difficile was cultured from the air with 23 samples yielding the bacterium (mean counts 53 – 426 cfu/m3 of air). One representative isolate from each of these was characterized further. Of the 23 isolates, 22 were ribotype 001 and were indistinguishable on REP-PCR typing. C. difficile was not cultured from the air or surfaces of either hospital bay during the two days in March 2007. Conclusion: This pilot study produced clear evidence of sporadic aerial dissemination of spores of a clone of C. difficile, a finding which may help to explain why CDAD is so persistent within hospitals and difficult to eradicate. Although preliminary, the findings reinforce concerns that current C. difficile control measures may be inadequate and suggest that improved ward ventilation may help to reduce the spread of CDAD in healthcare facilities

Variants in Hormone Biosynthesis Genes and Risk of Endometrial Cancer.

We investigated the risk associated with variants in three genes involved in estrogen biosynthesis, CYP11A1, CYP17A1, and CYP19A1, in the population-based case-control study of Estrogen, Diet, Genetics, and Endometrial Cancer. This study was conducted in New Jersey in 2001-2006 with 417 cases and 402 controls. For CYP11A1, there was no association between the number of [TTTTA]( n ) repeats (D15S520) and risk. For CYP17A1, risk was somewhat lower among women with the C/C genotype at T-34C (rs743572) (adjusted OR = 0.65, 95% CI 0.41-1.02). For CYP19A1, risk was lower among women homozygous for the 3-bp deletion (rs11575899) in exon 4 (adjusted OR = 0.44, 95% CI 0.26-0.76), while the number of [TTTA]( n ) repeats was not significantly related to risk: the adjusted OR for n = 7/7 repeats versus n \u3e 7/\u3e7 repeats was 0.81 (95% CI 0.54-1.23). In stratified analyses, results for CYP19A1 were stronger among women with higher (\u3e or =27.4) body mass index: for the homozygous deletion, OR = 0.30 (95% CI 0.15-0.62); for the n = 7/7 genotype, OR = 0.49 (95% CI 0.26-0.93). The interaction between the n = 7/7 genotype and BMI was statistically significant (p = 0.01). The insertion/deletion variant in CYP19A1 appears to be related to risk of endometrial cancer; risk associated with variants in this gene may vary according to BMI

Global change effects on plant communities are magnified by time and the number of global change factors imposed

Global change drivers (GCDs) are expected to alter community structure and consequently, the services that ecosystems provide. Yet, few experimental investigations have examined effects of GCDs on plant community structure across multiple ecosystem types, and those that do exist present conflicting patterns. In an unprecedented global synthesis of over 100 experiments that manipulated factors linked to GCDs, we show that herbaceous plant community responses depend on experimental manipulation length and number of factors manipulated. We found that plant communities are fairly resistant to experimentally manipulated GCDs in the short term (<10 y). In contrast, long-term (≥10 y) experiments show increasing community divergence of treatments from control conditions. Surprisingly, these community responses occurred with similar frequency across the GCD types manipulated in our database. However, community responses were more common when 3 or more GCDs were simultaneously manipulated, suggesting the emergence of additive or synergistic effects of multiple drivers, particularly over long time periods. In half of the cases, GCD manipulations caused a difference in community composition without a corresponding species richness difference, indicating that species reordering or replacement is an important mechanism of community responses to GCDs and should be given greater consideration when examining consequences of GCDs for the biodiversity–ecosystem function relationship. Human activities are currently driving unparalleled global changes worldwide. Our analyses provide the most comprehensive evidence to date that these human activities may have widespread impacts on plant community composition globally, which will increase in frequency over time and be greater in areas where communities face multiple GCDs simultaneously

Evolution of Genome Size and Complexity in Pinus

BACKGROUND: Genome evolution in the gymnosperm lineage of seed plants has given rise to many of the most complex and largest plant genomes, however the elements involved are poorly understood. METHODOLOGY/PRINCIPAL FINDINGS: Gymny is a previously undescribed retrotransposon family in Pinus that is related to Athila elements in Arabidopsis. Gymny elements are dispersed throughout the modern Pinus genome and occupy a physical space at least the size of the Arabidopsis thaliana genome. In contrast to previously described retroelements in Pinus, the Gymny family was amplified or introduced after the divergence of pine and spruce (Picea). If retrotransposon expansions are responsible for genome size differences within the Pinaceae, as they are in angiosperms, then they have yet to be identified. In contrast, molecular divergence of Gymny retrotransposons together with other families of retrotransposons can account for the large genome complexity of pines along with protein-coding genic DNA, as revealed by massively parallel DNA sequence analysis of Cot fractionated genomic DNA. CONCLUSIONS/SIGNIFICANCE: Most of the enormous genome complexity of pines can be explained by divergence of retrotransposons, however the elements responsible for genome size variation are yet to be identified. Genomic resources for Pinus including those reported here should assist in further defining whether and how the roles of retrotransposons differ in the evolution of angiosperm and gymnosperm genomes

Beyond ecosystem modeling: a roadmap to community cyberinfrastructure for ecological data‐model integration

In an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Bottlenecks to informing models with observations have reduced our capacity to fully exploit the growing volume and variety of available data. Here, we take a critical look at the information infrastructure that connects ecosystem modeling and measurement efforts, and propose a roadmap to community cyberinfrastructure development that can reduce the divisions between empirical research and modeling and accelerate the pace of discovery. A new era of data‐model integration requires investment in accessible, scalable, transparent tools that integrate the expertise of the whole community, including both modelers and empiricists. This roadmap focuses on five key opportunities for community tools: the underlying foundationsof community cyberinfrastructure; data ingest; calibration of models to data; model‐data benchmarking; and data assimilation and ecological forecasting. This community‐driven approach is key to meeting the pressing needs of science and society in the 21st century

Finding Diagnostically Useful Patterns in Quantitative Phenotypic Data.

Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a "phenotype first" approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

Germline mutations in ETV6 are associated with thrombocytopenia, red cell macrocytosis and predisposition to lymphoblastic leukemia

Some familial platelet disorders are associated with predisposition to leukemia, myelodysplastic syndrome (MDS) or dyserythropoietic anemia. We identified a family with autosomal dominant thrombocytopenia, high erythrocyte mean corpuscular volume (MCV) and two occurrences of B cell-precursor acute lymphoblastic leukemia (ALL). Whole-exome sequencing identified a heterozygous single-nucleotide change in ETV6 (ets variant 6), c.641C>T, encoding a p.Pro214Leu substitution in the central domain, segregating with thrombocytopenia and elevated MCV. A screen of 23 families with similar phenotypes identified 2 with ETV6 mutations. One family also had a mutation encoding p.Pro214Leu and one individual with ALL. The other family had a c.1252A>G transition producing a p.Arg418Gly substitution in the DNA-binding domain, with alternative splicing and exon skipping. Functional characterization of these mutations showed aberrant cellular localization of mutant and endogenous ETV6, decreased transcriptional repression and altered megakaryocyte maturation. Our findings underscore a key role for ETV6 in platelet formation and leukemia predisposition