Mass Cytometry Defines Virus-Specific CD4 + T Cells in Influenza Vaccination

The antiviral response to influenza virus is complex and multifaceted, involving many immune cell subsets. There is an urgent need to understand the role of CD4+ T cells, which orchestrate an effective antiviral response, to improve vaccine design strategies. In this study, we analyzed PBMCs from human participants immunized with influenza vaccine, using high-dimensional single-cell proteomic immune profiling by mass cytometry. Data were analyzed using a novel clustering algorithm, denoised ragged pruning, to define possible influenza virus-specific clusters of CD4+ T cells. Denoised ragged pruning identified six clusters of cells. Among these, one cluster (Cluster 3) was found to increase in abundance following stimulation with influenza virus peptide ex vivo. A separate cluster (Cluster 4) was found to expand in abundance between days 0 and 7 postvaccination, indicating that it is vaccine responsive. We examined the expression profiles of all six clusters to characterize their lineage, functionality, and possible role in the response to influenza vaccine. Clusters 3 and 4 consisted of effector memory cells, with high CD154 expression. Cluster 3 expressed cytokines like IL-2, IFN-γ, and TNF-α, whereas Cluster 4 expressed IL-17. Interestingly, some participants had low abundance of Clusters 3 and 4, whereas others had higher abundance of one of these clusters compared with the other. Taken together, we present an approach for identifying novel influenza virus-reactive CD4+ T cell subsets, a method that could help advance understanding of the immune response to influenza, predict responsiveness to vaccines, and aid in better vaccine design

Arthropod Distribution In A Tropical Rainforest: Tackling A Four Dimensional Puzzle

Quantifying the spatio-temporal distribution of arthropods in tropical rainforests represents a first step towards scrutinizing the global distribution of biodiversity on Earth. To date most studies have focused on narrow taxonomic groups or lack a design that allows partitioning of the components of diversity. Here, we consider an exceptionally large dataset (113,952 individuals representing 5,858 species), obtained from the San Lorenzo forest in Panama, where the phylogenetic breadth of arthropod taxa was surveyed using 14 protocols targeting the soil, litter, understory, lower and upper canopy habitats, replicated across seasons in 2003 and 2004. This dataset is used to explore the relative influence of horizontal, vertical and seasonal drivers of arthropod distribution in this forest. We considered arthropod abundance, observed and estimated species richness, additive decomposition of species richness, multiplicative partitioning of species diversity, variation in species composition, species turnover and guild structure as components of diversity. At the scale of our study (2km of distance, 40m in height and 400 days), the effects related to the vertical and seasonal dimensions were most important. Most adult arthropods were collected from the soil/litter or the upper canopy and species richness was highest in the canopy. We compared the distribution of arthropods and trees within our study system. Effects related to the seasonal dimension were stronger for arthropods than for trees. We conclude that: (1) models of beta diversity developed for tropical trees are unlikely to be applicable to tropical arthropods; (2) it is imperative that estimates of global biodiversity derived from mass collecting of arthropods in tropical rainforests embrace the strong vertical and seasonal partitioning observed here; and (3) given the high species turnover observed between seasons, global climate change may have severe consequences for rainforest arthropods.1012SolVin-Solvay SASTRIUnited Nations Environment ProgrammeSmithsonian Institution (Walcott Fund)European Science FoundationGlobal Canopy ProgrammeCzech Science foundation GACR grant [14-36098G]European Social FundCzech Ministry of Education [CZ.1.07/2.3.00/20.0064]U.S. National Science Fundation [DEB-0841885]Australian Research Council [FT100100040]Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)"Investissement d'Avenir'' grant [ANR-10-LABX-25-01]Norwegian Research CouncilGrant Agency of the Czech Republic [14-36098G

Treatment After Anterior Cruciate Ligament Injury: Panther Symposium ACL Treatment Consensus Group

© The Author(s) 2020. Treatment strategies for anterior cruciate ligament (ACL) injuries continue to evolve. Evidence supporting best-practice guidelines for the management of ACL injury is to a large extent based on studies with low-level evidence. An international consensus group of experts was convened to collaboratively advance toward consensus opinions regarding the best available evidence on operative versus nonoperative treatment for ACL injury. The purpose of this study was to report the consensus statements on operative versus nonoperative treatment of ACL injuries developed at the ACL Consensus Meeting Panther Symposium 2019. There were 66 international experts on the management of ACL injuries, representing 18 countries, who were convened and participated in a process based on the Delphi method of achieving consensus. Proposed consensus statements were drafted by the scientific organizing committee and session chairs for the 3 working groups. Panel participants reviewed preliminary statements before the meeting and provided initial agreement and comments on the statement via online survey. During the meeting, discussion and debate occurred for each statement, after which a final vote was then held. Ultimately, 80% agreement was defined a priori as consensus. A total of 11 of 13 statements on operative versus nonoperative treatment of ACL injury reached consensus during the symposium. Overall, 9 statements achieved unanimous support, 2 reached strong consensus, 1 did not achieve consensus, and 1 was removed because of redundancy in the information provided. In highly active patients engaged in jumping, cutting, and pivoting sports, early anatomic ACL reconstruction is recommended because of the high risk of secondary meniscal and cartilage injuries with delayed surgery, although a period of progressive rehabilitation to resolve impairments and improve neuromuscular function is recommended. For patients who seek to return to straight-plane activities, nonoperative treatment with structured, progressive rehabilitation is an acceptable treatment option. However, with persistent functional instability, or when episodes of giving way occur, anatomic ACL reconstruction is indicated. The consensus statements derived from international leaders in the field will assist clinicians in deciding between operative and nonoperative treatment with patients after an ACL injury

Genotypic variability enhances the reproducibility of an ecological study

Many scientific disciplines are currently experiencing a “reproducibility crisis” because numerous scientific findings cannot be repeated consistently. A novel but controversial hypothesis postulates that stringent levels of environmental and biotic standardization in experimental studies reduces reproducibility by amplifying impacts of lab-specific environmental factors not accounted for in study designs. A corollary to this hypothesis is that a deliberate introduction of controlled systematic variability (CSV) in experimental designs may lead to increased reproducibility. We tested this hypothesis using a multi-laboratory microcosm study in which the same ecological experiment was repeated in 14 laboratories across Europe. Each laboratory introduced environmental and genotypic CSV within and among replicated microcosms established in either growth chambers (with stringent control of environmental conditions) or glasshouses (with more variable environmental conditions). The introduction of genotypic CSV led to lower among-laboratory variability in growth chambers, indicating increased reproducibility, but had no significant effect in glasshouses where reproducibility was generally lower. Environmental CSV had little effect on reproducibility. Although there are multiple causes for the “reproducibility crisis”, deliberately including genetic variation may be a simple solution for increasing the reproducibility of ecological studies performed in controlled environments

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Design and implementation of a noise temperature measurement system for the Hydrogen Intensity and Real-time Analysis eXperiment (HIRAX)

This paper describes the design, implementation, and verification of a test-bed for determining the noise temperature of radio antennas operating between 400-800MHz. The requirements for this test-bed were driven by the HIRAX experiment, which uses antennas with embedded amplification, making system noise characterization difficult in the laboratory. The test-bed consists of two large cylindrical cavities, each containing radio-frequency (RF) absorber held at different temperatures (300K and 77K), allowing a measurement of system noise temperature through the well-known 'Y-factor' method. The apparatus has been constructed at Yale, and over the course of the past year has undergone detailed verification measurements. To date, three preliminary noise temperature measurement sets have been conducted using the system, putting us on track to make the first noise temperature measurements of the HIRAX feed and perform the first analysis of feed repeatability.Comment: 19 pages, 12 figure

Evaluation of polygenic risk scores for breast and ovarian cancer risk prediction in BRCA1 and BRCA2 mutation carriers

Background: Genome-wide association studies (GWAS) have identified 94 common single-nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk and 18 associated with ovarian cancer (OC) risk. Several of these are also associated with risk of BC or OC for women who carry a pathogenic mutation in the high-risk BC and OC genes BRCA1 or BRCA2. The combined effects of these variants on BC or OC risk for BRCA1 and BRCA2 mutation carriers have not yet been assessed while their clinical management could benefit from improved personalized risk estimates. Methods: We constructed polygenic risk scores (PRS) using BC and OC susceptibility SNPs identified through population-based GWAS: for BC (overall, estrogen receptor [ER]-positive, and ER-negative) and for OC. Using data from 15 252 female BRCA1 and 8211 BRCA2 carriers, the association of each PRS with BC or OC risk was evaluated using a weighted cohort approach, with time to diagnosis as the outcome and estimation of the hazard ratios (HRs) per standard deviation increase in the PRS. Results: The PRS for ER-negative BC displayed the strongest association with BC risk in BRCA1 carriers (HR = 1.27, 95% confidence interval [CI] = 1.23 to 1.31, P = 8.2 x 10(53)). In BRCA2 carriers, the strongest association with BC risk was seen for the overall BC PRS (HR = 1.22, 95% CI = 1.17 to 1.28, P = 7.2 x 10(-20)). The OC PRS was strongly associated with OC risk for both BRCA1 and BRCA2 carriers. These translate to differences in absolute risks (more than 10% in each case) between the top and bottom deciles of the PRS distribution; for example, the OC risk was 6% by age 80 years for BRCA2 carriers at the 10th percentile of the OC PRS compared with 19% risk for those at the 90th percentile of PRS. Conclusions: BC and OC PRS are predictive of cancer risk in BRCA1 and BRCA2 carriers. Incorporation of the PRS into risk prediction models has promise to better inform decisions on cancer risk management

A chemical survey of exoplanets with ARIEL

Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25–7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10–100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.Peer reviewedFinal Published versio