From sink to source: long-term (2002-2019) trends and anomalies in net ecosystem exchange of CO2 from a Scottish temperate peatland

A 'display' at the EGU General Assembly 2020. Peatlands North of 45˚ represent one of the largest terrestrial carbon (C) stores. They play an important role in the global C-cycle, and their ability to sequester carbon is controlled by multiple, often competing, factors including precipitation, temperature and phenology. Land-atmosphere exchange of carbon dioxide (CO2) is dynamic, and exhibits marked seasonal and inter-annual variations which can effect the overall carbon sink strength in both the short- and long-term. Due to increased incidences of climate anomalies in recent years, long-term datasets are essential to disambiguate natural variability in Net Ecosystem Exchange (NEE) from shorter-term fluctuations. This is particularly important at high latitudes (>45˚N) where the majority of global peatlands are found. With increasing pressure from stressors such as climate and land-use change, it has been predicted that with a ca. 3oC global temperature rise by 2100, UK peatlands could become a net source of C. NEE of CO2 has been measured using the eddy-covariance (EC) method at Auchencorth Moss (55°47’32 N, 3°14’35 W, 267 m a.s.l.), a temperate, lowland, ombrotrophic peatland in central Scotland, continuously since 2002. Alongside EC data, we present a range of meteorological parameters measured at site including soil temperature, total solar and photosynthetically active radiation (PAR), rainfall, and, since April 2007, half-hourly water table depth readings. The length of record and range of measurements make this dataset an important resource as one of the longest term records of CO2 fluxes from a temperate peatland. Although seasonal cycles of gross primary productivity (GPP) were highly variable between years, the site was a consistent CO2 sink for the period 2002-2012. However, net annual losses of CO2 have been recorded on several occasions since 2013. Whilst NEE tends to be positively correlated with the length of growing season, anomalies in winter weather also explain some of the variability in CO2 sink strength the following summer. Additionally, water table depth (WTD) plays a crucial role, affecting both GPP and ecosystem respiration (Reco). Relatively dry summers in recent years have contributed to shifting the balance between Reco and GPP: prolonged periods of low WTD were typically accompanied by an increase in Reco, and a decrease in GPP, hence weakening the overall CO2 sink strength. Extreme events such as drought periods and cold winter temperatures can have significant and complex effects on NEE, particularly when such meteorological anomalies co-occur. For example, a positive annual NEE occurred in 2003 when Europe experienced heatwave and summer drought. More recently, an unusually long spell of snow lasting until the end of March delayed the onset of the 2018 growing season by up to 1.5 months compared to previous years. This was followed by a prolonged dry spell in summer 2018, which weakened GPP, increased Reco and led to a net annual loss of 47.4 ton CO2-C km-2. It is clear that the role of Northern peatlands within the carbon cycle is being modified, driven by changes in climate at both local and global scales

UKCEH at the Climate Science Showcase – Dynamic Earth, Edinburgh, 6th November 2021

In total over 250 people engaged with the UKCEH Team at the Dynamic Earth hosted Climate Science Showcase on Saturday 6th November 2021 between 10 am and 4 pm (~40 h-1). The stand fulfilled its aim to raise awareness of publicly funded research conducted at UKCEH Edinburgh, including the national capability project UK Status, Change and Projections of the Environment (UK-SCAPE), as evidenced by the large number of people attracted into the stand, the remarks made in conversations with the team members and written in the answers to the wishing tree

Two-year efficacy and safety of risdiplam in patients with type 2 or non-ambulant type 3 spinal muscular atrophy (SMA)

Risdiplam is an oral, survival of motor neuron 2 (SMN2) pre-mRNA splicing modifier approved for the treatment of spinal muscular atrophy (SMA). SUNFISH (NCT02908685) Part 2, a Phase 3, randomized, double-blind, placebo-controlled study, investigated the efficacy and safety of risdiplam in type 2 and non‑ambulant type 3 SMA. The primary endpoint was met: a significantly greater change from baseline in 32-item Motor Function Measure (MFM32) total score was observed with risdiplam compared with placebo at month 12. After 12 months, all participants received risdiplam while preserving initial treatment blinding. We report 24-month efficacy and safety results in this population. Month 24 exploratory endpoints included change from baseline in MFM32 and safety. MFM‑derived results were compared with an external comparator. At month 24 of risdiplam treatment, 32% of patients demonstrated improvement (a change of ≥ 3) from baseline in MFM32 total score; 58% showed stabilization (a change of ≥ 0). Compared with an external comparator, a treatment difference of 3.12 (95% confidence interval [CI] 1.67-4.57) in favor of risdiplam was observed in MFM-derived scores. Overall, gains in motor function at month 12 were maintained or improved upon at month 24. In patients initially receiving placebo, MFM32 remained stable compared with baseline (0.31 [95% CI - 0.65 to 1.28]) after 12 months of risdiplam; 16% of patients improved their score and 59% exhibited stabilization. The safety profile after 24 months was consistent with that observed after 12 months. Risdiplam over 24 months resulted in further improvement or stabilization in motor function, confirming the benefit of longer-term treatment

Polymers for Improving the In Vivo Transduction Efficiency of AAV2 Vectors

Background: Adeno-associated virus has attracted great attention as vehicle for body-wide gene delivery. However, for the successful treatment of a disease such as Duchenne muscular dystrophy infusion of very large amounts of vectors is required. This not only raises questions about the technical feasibility of the large scale production but also about the overall safety of the approach. One way to overcome these problems would be to find strategies able to increase the in vivo efficiency. Methodology: Here, we investigated whether polymers can act as adjuvants to increase the in vivo efficiency of AAV2. Our strategy consisted in the pre-injection of polymers before intravenous administration of mice with AAV2 encoding a murine secreted alkaline phosphatase (mSeAP). The transgene expression, vector biodistribution and tissue transduction were studied by quantification of the mSeAP protein and real time PCR. The injection of polyinosinic acid and polylysine resulted in an increase of plasmatic mSeAP of 2- and 12-fold, respectively. Interestingly, polyinosinic acid pre-injection significantly reduced the neutralizing antibody titer raised against AAV2. Conclusions: Our results show that the pre-injection of polymers can improve the overall transduction efficiency of systemically administered AAV2 and reduce the humoral response against the capsid proteins

DataPerf: Benchmarks for Data-Centric AI Development

Machine learning research has long focused on models rather than datasets, and prominent datasets are used for common ML tasks without regard to the breadth, difficulty, and faithfulness of the underlying problems. Neglecting the fundamental importance of data has given rise to inaccuracy, bias, and fragility in real-world applications, and research is hindered by saturation across existing dataset benchmarks. In response, we present DataPerf, a community-led benchmark suite for evaluating ML datasets and data-centric algorithms. We aim to foster innovation in data-centric AI through competition, comparability, and reproducibility. We enable the ML community to iterate on datasets, instead of just architectures, and we provide an open, online platform with multiple rounds of challenges to support this iterative development. The first iteration of DataPerf contains five benchmarks covering a wide spectrum of data-centric techniques, tasks, and modalities in vision, speech, acquisition, debugging, and diffusion prompting, and we support hosting new contributed benchmarks from the community. The benchmarks, online evaluation platform, and baseline implementations are open source, and the MLCommons Association will maintain DataPerf to ensure long-term benefits to academia and industry.Comment: NeurIPS 2023 Datasets and Benchmarks Trac

Evolutionary Reconstructions of the Transferrin Receptor of Caniforms Supports Canine Parvovirus Being a Re-emerged and Not a Novel Pathogen in Dogs

Parvoviruses exploit transferrin receptor type-1 (TfR) for cellular entry in carnivores, and specific interactions are key to control of host range. We show that several key mutations acquired by TfR during the evolution of Caniforms (dogs and related species) modified the interactions with parvovirus capsids by reducing the level of binding. These data, along with signatures of positive selection in the TFRC gene, are consistent with an evolutionary arms race between the TfR of the Caniform clade and parvoviruses. As well as the modifications of amino acid sequence which modify binding, we found that a glycosylation site mutation in the TfR of dogs which provided resistance to the carnivore parvoviruses which were in circulation prior to about 1975 predates the speciation of coyotes and dogs. Because the closely-related black-backed jackal has a TfR similar to their common ancestor and lacks the glycosylation site, reconstructing this mutation into the jackal TfR shows the potency of that site in blocking binding and infection and explains the resistance of dogs until recent times. This alters our understanding of this well-known example of viral emergence by indicating that canine parvovirus emergence likely resulted from the re-adaptation of a parvovirus to the resistant receptor of a former host

A meta-analysis of genome-wide association studies for serum total IgE in diverse study populations

Background: Immunoglobulin E (IgE) is both a marker and mediator of allergic inflammation. Despite reported differences in serum total IgE levels by race-ethnicity, African American and Latino individuals have not been well represented in genetic studies of total IgE. Objective: To identify the genetic predictors of serum total IgE levels. Methods: We used genome wide association (GWA) data from 4,292 individuals (2,469 African Americans, 1,564 European Americans, and 259 Latinos) in the EVE Asthma Genetics Consortium. Tests for association were performed within each cohort by race-ethnic group (i.e., African American, Latino, and European American) and asthma status. The resulting p-values were meta-analyzed accounting for sample size and direction of effect. Top single nucleotide polymorphism (SNP) associations from the meta-analysis were reassessed in six additional cohorts comprising 5,767 individuals. Results: We identified 10 unique regions where the combined association statistic was associated with total serum IgE levels (P-value <5.0×10−6) and the minor allele frequency was ≥5% in two or more population groups. Variant rs9469220, corresponding to HLA-DQB1, was the most significantly associated SNP with serum total IgE levels when assessed in both the replication cohorts and the discovery and replication sets combined (P-value = 0.007 and 2.45×10−7, respectively). In addition, findings from earlier GWA studies were also validated in the current meta-analysis. Conclusion: This meta-analysis independently identified a variant near HLA-DQB1 as a predictor of total serum IgE in multiple race-ethnic groups. This study also extends and confirms the findings of earlier GWA analyses in African American and Latino individuals

A meta-analysis of genome-wide association studies for serum total IgE in diverse study populations

BACKGROUND: Immunoglobulin E (IgE) is both a marker and mediator of allergic inflammation. Despite reported differences in serum total IgE levels by race-ethnicity, African American and Latino individuals have not been well represented in genetic studies of total IgE. OBJECTIVE: To identify the genetic predictors of serum total IgE levels. METHODS: We used genome wide association (GWA) data from 4,292 individuals (2,469 African Americans, 1,564 European Americans, and 259 Latinos) in the EVE Asthma Genetics Consortium. Tests for association were performed within each cohort by race-ethnic group (i.e., African American, Latino, and European American) and asthma status. The resulting p-values were meta-analyzed accounting for sample size and direction of effect. Top single nucleotide polymorphism (SNP) associations from the meta-analysis were reassessed in six additional cohorts comprising 5,767 individuals. RESULTS: We identified 10 unique regions where the combined association statistic was associated with total serum IgE levels (P-value <5.0×10(−6)) and the minor allele frequency was ≥5% in two or more population groups. Variant rs9469220, corresponding to HLA-DQB1, was the most significantly associated SNP with serum total IgE levels when assessed in both the replication cohorts and the discovery and replication sets combined (P-value = 0.007 and 2.45×10(−7), respectively). In addition, findings from earlier GWA studies were also validated in the current meta-analysis. CONCLUSION: This meta-analysis independently identified a variant near HLA-DQB1 as a predictor of total serum IgE in multiple race-ethnic groups. This study also extends and confirms the findings of earlier GWA analyses in African American and Latino individuals