Effects of the 2017 Solar Eclipse on HF Radio Propagation and the D-Region Ionosphere: Citizen Science Investigation

August 21, 2017 provided a unique opportunity to investigate the effects of the total solar eclipse on high frequency (HF) radio propagation and ionospheric variability. In Marshall Space Flight Center's partnership with the US Space and Rocket Center (USSRC) and Austin Peay State University (APSU), we engaged students and citizen scientists in an investigation of the eclipse effects on the mid-latitude ionosphere. Activities included implementing and configuring software, monitoring the HF Amateur Radio frequency bands and collecting radio transmission data on days before, the day of, and days after the eclipse to build a continuous record of changing propagation conditions as the moon's shadow marched across the United States. Post-eclipse radio propagation analysis provided insights into ionospheric variability due to the eclipse. We report on results, interpretation, and conclusions of these investigations

The 2dF-SDSS LRG and QSO survey: evolution of the clustering of luminous red galaxies since z = 0.6

We present an analysis of the small-to-intermediate scale clustering of samples of Luminous Red Galaxies (LRGs) from the Sloan Digital Sky Survey and the 2dF-SDSS LRG and QSO (2SLAQ) survey carefully matched to have the same rest-frame colours and luminosity. We study the spatial two-point auto-correlation function in both redshift-space and real-space of a combined sample of over 10,000 LRGs, which represent the most massive galaxies in the universe with stellar masses > 10^11 h^-1 M_sun and space densities 10^-4 h^-3 Mpc^-3. We find no significant evolution in the amplitude r_0 of the correlation function with redshift, but do see a slight decrease in the slope with increasing redshift over 0.19 < z < 0.55 and scales of 0.32 < r < 32 h^-1 Mpc. We compare our measurements with the predicted evolution of dark matter clustering and use the halo model to interpret our results. We find that our clustering measurements are inconsistent (>99.9% significance) with a passive model whereby the LRGs do not merge with one another; a model with a merger rate of 7.5 +/- 2.3% from z = 0.55 to z = 0.19 (i.e. an average rate of 2.4% Gyr^-1) provides a better fit to our observations. Our clustering and number density measurements are consistent with the hypothesis that the merged LRGs were originally central galaxies in different haloes which, following the merger of these haloes, merged to create a single Brightest Cluster Galaxy. In addition, we show that the small-scale clustering signal constrains the scatter in halo merger histories. When combined with measurements of the luminosity function, our results suggest that this scatter is sub-Poisson. While this is a generic prediction of hierarchical models, it has not been tested before.Comment: 20 pages, replaced with version accepted for publication in MNRA

Trends in invasive bacterial diseases during the first 2 years of the COVID-19 pandemic: analyses of prospective surveillance data from 30 countries and territories in the IRIS Consortium.

BACKGROUND The Invasive Respiratory Infection Surveillance (IRIS) Consortium was established to assess the impact of the COVID-19 pandemic on invasive diseases caused by Streptococcus pneumoniae, Haemophilus influenzae, Neisseria meningitidis, and Streptococcus agalactiae. We aimed to analyse the incidence and distribution of these diseases during the first 2 years of the COVID-19 pandemic compared to the 2 years preceding the pandemic. METHODS For this prospective analysis, laboratories in 30 countries and territories representing five continents submitted surveillance data from Jan 1, 2018, to Jan 2, 2022, to private projects within databases in PubMLST. The impact of COVID-19 containment measures on the overall number of cases was analysed, and changes in disease distributions by patient age and serotype or group were examined. Interrupted time-series analyses were done to quantify the impact of pandemic response measures and their relaxation on disease rates, and autoregressive integrated moving average models were used to estimate effect sizes and forecast counterfactual trends by hemisphere. FINDINGS Overall, 116 841 cases were analysed: 76 481 in 2018-19, before the pandemic, and 40 360 in 2020-21, during the pandemic. During the pandemic there was a significant reduction in the risk of disease caused by S pneumoniae (risk ratio 0·47; 95% CI 0·40-0·55), H influenzae (0·51; 0·40-0·66) and N meningitidis (0·26; 0·21-0·31), while no significant changes were observed for S agalactiae (1·02; 0·75-1·40), which is not transmitted via the respiratory route. No major changes in the distribution of cases were observed when stratified by patient age or serotype or group. An estimated 36 289 (95% prediction interval 17 145-55 434) cases of invasive bacterial disease were averted during the first 2 years of the pandemic among IRIS-participating countries and territories. INTERPRETATION COVID-19 containment measures were associated with a sustained decrease in the incidence of invasive disease caused by S pneumoniae, H influenzae, and N meningitidis during the first 2 years of the pandemic, but cases began to increase in some countries towards the end of 2021 as pandemic restrictions were lifted. These IRIS data provide a better understanding of microbial transmission, will inform vaccine development and implementation, and can contribute to health-care service planning and provision of policies. FUNDING Wellcome Trust, NIHR Oxford Biomedical Research Centre, Spanish Ministry of Science and Innovation, Korea Disease Control and Prevention Agency, Torsten Söderberg Foundation, Stockholm County Council, Swedish Research Council, German Federal Ministry of Health, Robert Koch Institute, Pfizer, Merck, and the Greek National Public Health Organization

HMOX1 Gene Promoter Alleles and High HO-1 Levels Are Associated with Severe Malaria in Gambian Children

Heme oxygenase 1 (HO-1) is an essential enzyme induced by heme and multiple stimuli associated with critical illness. In humans, polymorphisms in the HMOX1 gene promoter may influence the magnitude of HO-1 expression. In many diseases including murine malaria, HO-1 induction produces protective anti-inflammatory effects, but observations from patients suggest these may be limited to a narrow range of HO-1 induction, prompting us to investigate the role of HO-1 in malaria infection. In 307 Gambian children with either severe or uncomplicated P. falciparum malaria, we characterized the associations of HMOX1 promoter polymorphisms, HMOX1 mRNA inducibility, HO-1 protein levels in leucocytes (flow cytometry), and plasma (ELISA) with disease severity. The (GT)n repeat polymorphism in the HMOX1 promoter was associated with HMOX1 mRNA expression in white blood cells in vitro, and with severe disease and death, while high HO-1 levels were associated with severe disease. Neutrophils were the main HO-1-expressing cells in peripheral blood, and HMOX1 mRNA expression was upregulated by heme-moieties of lysed erythrocytes. We provide mechanistic evidence that induction of HMOX1 expression in neutrophils potentiates the respiratory burst, and propose this may be part of the causal pathway explaining the association between short (GT)n repeats and increased disease severity in malaria and other critical illnesses. Our findings suggest a genetic predisposition to higher levels of HO-1 is associated with severe illness, and enhances the neutrophil burst leading to oxidative damage of endothelial cells. These add important information to the discussion about possible therapeutic manipulation of HO-1 in critically ill patients

Targeted Next-Generation Sequencing Analysis of 1,000 Individuals with Intellectual Disability.

To identify genetic causes of intellectual disability (ID), we screened a cohort of 986 individuals with moderate to severe ID for variants in 565 known or candidate ID-associated genes using targeted next-generation sequencing. Likely pathogenic rare variants were found in ∼11% of the cases (113 variants in 107/986 individuals: ∼8% of the individuals had a likely pathogenic loss-of-function [LoF] variant, whereas ∼3% had a known pathogenic missense variant). Variants in SETD5, ATRX, CUL4B, MECP2, and ARID1B were the most common causes of ID. This study assessed the value of sequencing a cohort of probands to provide a molecular diagnosis of ID, without the availability of DNA from both parents for de novo sequence analysis. This modeling is clinically relevant as 28% of all UK families with dependent children are single parent households. In conclusion, to diagnose patients with ID in the absence of parental DNA, we recommend investigation of all LoF variants in known genes that cause ID and assessment of a limited list of proven pathogenic missense variants in these genes. This will provide 11% additional diagnostic yield beyond the 10%-15% yield from array CGH alone.Action Medical Research (SP4640); the Birth Defect Foundation (RG45448); the Cambridge National Institute for Health Research Biomedical Research Centre (RG64219); the NIHR Rare Diseases BioResource (RBAG163); Wellcome Trust award WT091310; The Cell lines and DNA bank of Rett Syndrome, X-linked mental retardation and other genetic diseases (member of the Telethon Network of Genetic Biobanks (project no. GTB12001); the Genetic Origins of Congenital Heart Disease Study (GO-CHD)- funded by British Heart Foundation (BHF)This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/humu.2290

Prevalence and architecture of de novo mutations in developmental disorders.

The genomes of individuals with severe, undiagnosed developmental disorders are enriched in damaging de novo mutations (DNMs) in developmentally important genes. Here we have sequenced the exomes of 4,293 families containing individuals with developmental disorders, and meta-analysed these data with data from another 3,287 individuals with similar disorders. We show that the most important factors influencing the diagnostic yield of DNMs are the sex of the affected individual, the relatedness of their parents, whether close relatives are affected and the parental ages. We identified 94 genes enriched in damaging DNMs, including 14 that previously lacked compelling evidence of involvement in developmental disorders. We have also characterized the phenotypic diversity among these disorders. We estimate that 42% of our cohort carry pathogenic DNMs in coding sequences; approximately half of these DNMs disrupt gene function and the remainder result in altered protein function. We estimate that developmental disorders caused by DNMs have an average prevalence of 1 in 213 to 1 in 448 births, depending on parental age. Given current global demographics, this equates to almost 400,000 children born per year

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives