VaxCelerate II: Rapid development of a self-assembling vaccine for Lassa fever

Development of effective vaccines against emerging infectious diseases (EID) can take as much or more than a decade to progress from pathogen isolation/identification to clinical approval. As a result, conventional approaches fail to produce field-ready vaccines before the EID has spread extensively. Lassa is a prototypical emerging infectious disease endemic to West Africa for which no successful vaccine is available. We established the VaxCelerate Consortium to address the need for more rapid vaccine development by creating a platform capable of generating and pre-clinically testing a new vaccine against specific pathogen targets in less than 120 d. A self-assembling vaccine is at the core of the approach. It consists of a fusion protein composed of the immunostimulatory Mycobacterium tuberculosis heat shock protein 70 (MtbHSP70) and the biotin binding protein, avidin. Mixing the resulting protein (MAV) with biotinylated pathogen-specific immunogenic peptides yields a self-assembled vaccine (SAV). To meet the time constraint imposed on this project, we used a distributed R&D model involving experts in the fields of protein engineering and production, bioinformatics, peptide synthesis/design and GMP/GLP manufacturing and testing standards. SAV immunogenicity was first tested using H1N1 influenza specific peptides and the entire VaxCelerate process was then tested in a mock live-fire exercise targeting Lassa fever virus. We demonstrated that the Lassa fever vaccine induced significantly increased class II peptide specific interferon-γ CD4+ T cell responses in HLA-DR3 transgenic mice compared to peptide or MAV alone controls. We thereby demonstrated that our SAV in combination with a distributed development model may facilitate accelerated regulatory review by using an identical design for each vaccine and by applying safety and efficacy assessment tools that are more relevant to human vaccine responses than current animal models

Genetic diversity and connectivity of southern right whales (Eubalaena australis) found in the Brazil and Chile-Peru wintering grounds and the South Georgia (Islas Georgias del Sur) feeding ground

As species recover from exploitation, continued assessments of connectivity and population structure are warranted to provide information for conservation and management. This is particularly true in species with high dispersal capacity, such as migratory whales, where patterns of connectivity could change rapidly. Here we build on a previous long-term, large-scale collaboration on southern right whales (Eubalaena australis) to combine new (nnew) and published (npub) mitochondrial (mtDNA) and microsatellite genetic data from all major wintering grounds and, uniquely, the South Georgia (Islas Georgias del Sur: SG) feeding grounds. Specifically, we include data from Argentina (npub mtDNA/microsatellite=208/46), Brazil (nnew mtDNA/microsatellite=50/50), South Africa (nnew mtDNA/microsatellite=66/77, npub mtDNA/microsatellite=350/47), Chile-Peru (nnew mtDNA/microsatellite=1/1), the Indo-Pacific (npub mtDNA/microsatellite=769/126), and SG (npub mtDNA/microsatellite=8/0, nnew mtDNA/microsatellite=3/11) to investigate the position of previously unstudied habitats in the migratory network: Brazil, SG and Chile-Peru. These new genetic data show connectivity between Brazil and Argentina, exemplified by weak genetic differentiation and the movement of one genetically identified individual between the South American grounds. The single sample from Chile-Peru had a mtDNA haplotype previously only observed in the Indo-Pacific and had a nuclear genotype that appeared admixed between the Indo-Pacific and South Atlantic, based on genetic clustering and assignment algorithms. The SG samples were clearly South Atlantic, and were more similar to the South American than the South African wintering grounds. This study highlights how international collaborations are critical to provide context for emerging or recovering regions, like the SG feeding ground, as well as those that remain critically endangered, such as Chile-Peru

ECOSTRESS: NASA's next generation mission to measure evapotranspiration from the International Space Station

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station ECOSTRESS) was launched to the International Space Station on June 29, 2018. The primary science focus of ECOSTRESS is centered on evapotranspiration (ET), which is produced as level‐3 (L3) latent heat flux (LE) data products. These data are generated from the level‐2 land surface temperature and emissivity product (L2_LSTE), in conjunction with ancillary surface and atmospheric data. Here, we provide the first validation (Stage 1, preliminary) of the global ECOSTRESS clear‐sky ET product (L3_ET_PT‐JPL, version 6.0) against LE measurements at 82 eddy covariance sites around the world. Overall, the ECOSTRESS ET product performs well against the site measurements (clear‐sky instantaneous/time of overpass: r2 = 0.88; overall bias = 8%; normalized RMSE = 6%). ET uncertainty was generally consistent across climate zones, biome types, and times of day (ECOSTRESS samples the diurnal cycle), though temperate sites are over‐represented. The 70 m high spatial resolution of ECOSTRESS improved correlations by 85%, and RMSE by 62%, relative to 1 km pixels. This paper serves as a reference for the ECOSTRESS L3 ET accuracy and Stage 1 validation status for subsequent science that follows using these data

Implications for sequencing of biologic therapy and choice of second anti-TNF in patients with inflammatory bowel disease:results from the IMmunogenicity to Second Anti-TNF therapy (IMSAT) therapeutic drug monitoring study

BACKGROUND: Anti-drug antibodies are associated with treatment failure to anti-TNF agents in patients with inflammatory bowel disease (IBD).AIM: To assess whether immunogenicity to a patient's first anti-TNF agent would be associated with immunogenicity to the second, irrespective of drug sequence METHODS: We conducted a UK-wide, multicentre, retrospective cohort study to report rates of immunogenicity and treatment failure of second anti-TNF therapies in 1058 patients with IBD who underwent therapeutic drug monitoring for both infliximab and adalimumab. The primary outcome was immunogenicity to the second anti-TNF agent, defined at any timepoint as an anti-TNF antibody concentration ≥9 AU/ml for infliximab and ≥6 AU/ml for adalimumab.RESULTS: In patients treated with infliximab and then adalimumab, those who developed antibodies to infliximab were more likely to develop antibodies to adalimumab, than patients who did not develop antibodies to infliximab (OR 1.99, 95%CI 1.27-3.20, p = 0.002). Similarly, in patients treated with adalimumab and then infliximab, immunogenicity to adalimumab was associated with subsequent immunogenicity to infliximab (OR 2.63, 95%CI 1.46-4.80, p < 0.001). For each 10-fold increase in anti-infliximab and anti-adalimumab antibody concentration, the odds of subsequently developing antibodies to adalimumab and infliximab increased by 1.73 (95% CI 1.38-2.17, p < 0.001) and 1.99 (95%CI 1.34-2.99, p < 0.001), respectively. Patients who developed immunogenicity with undetectable drug levels to infliximab were more likely to develop immunogenicity with undetectable drug levels to adalimumab (OR 2.37, 95% CI 1.39-4.19, p < 0.001). Commencing an immunomodulator at the time of switching to the second anti-TNF was associated with improved drug persistence in patients with immunogenic, but not pharmacodynamic failure.CONCLUSION: Irrespective of drug sequence, immunogenicity to the first anti-TNF agent was associated with immunogenicity to the second, which was mitigated by the introduction of an immunomodulator in patients with immunogenic, but not pharmacodynamic treatment failure

Implications for sequencing of biologic therapy and choice of second anti-TNF in patients with inflammatory bowel disease:results from the IMmunogenicity to Second Anti-TNF therapy (IMSAT) therapeutic drug monitoring study

BACKGROUND: Anti-drug antibodies are associated with treatment failure to anti-TNF agents in patients with inflammatory bowel disease (IBD).AIM: To assess whether immunogenicity to a patient's first anti-TNF agent would be associated with immunogenicity to the second, irrespective of drug sequence METHODS: We conducted a UK-wide, multicentre, retrospective cohort study to report rates of immunogenicity and treatment failure of second anti-TNF therapies in 1058 patients with IBD who underwent therapeutic drug monitoring for both infliximab and adalimumab. The primary outcome was immunogenicity to the second anti-TNF agent, defined at any timepoint as an anti-TNF antibody concentration ≥9 AU/ml for infliximab and ≥6 AU/ml for adalimumab.RESULTS: In patients treated with infliximab and then adalimumab, those who developed antibodies to infliximab were more likely to develop antibodies to adalimumab, than patients who did not develop antibodies to infliximab (OR 1.99, 95%CI 1.27-3.20, p = 0.002). Similarly, in patients treated with adalimumab and then infliximab, immunogenicity to adalimumab was associated with subsequent immunogenicity to infliximab (OR 2.63, 95%CI 1.46-4.80, p < 0.001). For each 10-fold increase in anti-infliximab and anti-adalimumab antibody concentration, the odds of subsequently developing antibodies to adalimumab and infliximab increased by 1.73 (95% CI 1.38-2.17, p < 0.001) and 1.99 (95%CI 1.34-2.99, p < 0.001), respectively. Patients who developed immunogenicity with undetectable drug levels to infliximab were more likely to develop immunogenicity with undetectable drug levels to adalimumab (OR 2.37, 95% CI 1.39-4.19, p < 0.001). Commencing an immunomodulator at the time of switching to the second anti-TNF was associated with improved drug persistence in patients with immunogenic, but not pharmacodynamic failure.CONCLUSION: Irrespective of drug sequence, immunogenicity to the first anti-TNF agent was associated with immunogenicity to the second, which was mitigated by the introduction of an immunomodulator in patients with immunogenic, but not pharmacodynamic treatment failure

Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (similar to 25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available

Global data on earthworm abundance, biomass, diversity and corresponding environmental properties

Publisher Copyright: © 2021, The Author(s).Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ecological groups. This global dataset contains 10,840 sites, with 184 species, from 60 countries and all continents except Antarctica. The data were obtained from 182 published articles, published between 1973 and 2017, and 17 unpublished datasets. Amalgamating data into a single global database will assist researchers in investigating and answering a wide variety of pressing questions, for example, jointly assessing aboveground and belowground biodiversity distributions and drivers of biodiversity change.Peer reviewe

Global data on earthworm abundance, biomass, diversity and corresponding environmental properties

Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ecological groups. This global dataset contains 10,840 sites, with 184 species, from 60 countries and all continents except Antarctica. The data were obtained from 182 published articles, published between 1973 and 2017, and 17 unpublished datasets. Amalgamating data into a single global database will assist researchers in investigating and answering a wide variety of pressing questions, for example, jointly assessing aboveground and belowground biodiversity distributions and drivers of biodiversity change