Development and use of lentiviral vectors pseudotyped with influenza B haemagglutinins: application to vaccine immunogenicity, mAb potency and sero-surveillance studies

Influenza B viruses cause respiratory disease epidemics in human populations and are included in seasonal influenza vaccines. Serological methods are employed to evaluate vaccine immunogenicity prior to licensure. However, the haemagglutination inhibition assay, which represents the gold standard for assessing the immunogenicity of influenza vaccines, has been shown to be relatively insensitive for the detection of antibodies against influenza B viruses. Furthermore, this assay, and the serial radial haemolysis assay are not able to detect stalk-directed cross-reactive antibodies. For these reasons there is a need to develop new assays that can overcome these limitations. The use of replication-defective viruses, such as lentiviral vectors pseudotyped with influenza A haemagglutinins, in microneutralization assays is a safe and sensitive alternative to study antibody responses elicited by natural infection or vaccination. We have produced Influenza B haemagglutinin-pseudotypes using plasmid-directed transfection. To activate influenza B haemagglutinin, we have explored the use of proteases by adding relevant encoding plasmids to the transfection mixture. When tested for their ability to transduce target cells, the newly produced influenza B pseudotypes exhibit tropism for different cell lines. Subsequently the pseudotypes were evaluated as surrogate antigens in microneutralization assays using reference sera, monoclonal antibodies, human sera collected during a vaccine immunogenicity study and surveillance sera from seals. The influenza B pseudotype virus neutralization assay was found to effectively detect neutralizing and cross-reactive responses despite lack of significant correlation with the haemagglutinin inhibition assay

Synthetic Nitrogen Fertiliser in South Asia: Production, Import, Export, and Use for Crops, South Asia Nitrogen Hub (SANH) Policy Brief

This policy brief is produced by the UKRI GCRF South Asian Nitrogen Hub (SANH). It provides an overview of the patterns and trends in synthetic nitrogen (N) fertiliser use in crop production, import, export and emission in the South Asian Region (SAR) and its member countries; Afghanistan, Bangladesh, Bhutan, Nepal, India, Maldives, Pakistan, and Sri Lanka. In summary, reactive nitrogen (Nr) in fertilisers is essential for meeting global food and animal feed demands, but Nr pollution has become a major environmental issue across all scales. For SAR, inefficient use of synthetic N fertiliser is a key factor contributing to water pollution, air pollution, climate change, biodiversity loss and soil degradation. Further insights are provided on major fertiliser products, as well as in crop production, import and export. These data are essential for informing and promoting sustainable nitrogen management. Evidence based policy is more important than ever. The SANH is supported by UK Research and Innovation (UKRI) through its Global Challenge Research Fund (GCRF) to gather evidence on nitrogen issues to support countries in the South Asian Region (SAR) comprising eight countries (Nepal, Bangladesh, Pakistan, India, Bhutan, Sri Lanka, Afghanistan, and Maldives) to identify solutions and reduce nitrogen waste. SANH is pioneering a UK-SAR research partnership to catalyse transformational change in SAR to tackle the nitrogen challenge, benefi ting the economy, people’s health and the environment. SANH brings together 32 leading research organisations with governments and other partners. This policy brief provides key insights into national fertiliser trends for all eight SAR countries

Synthetic Nitrogen Fertiliser in South Asia: Production, Import, Export, and Use for Crops, South Asia Nitrogen Hub (SANH) Policy Brief

This policy brief is produced by the UKRI GCRF South Asian Nitrogen Hub (SANH). It provides an overview of the patterns and trends in synthetic nitrogen (N) fertiliser use in crop production, import, export and emission in the South Asian Region (SAR) and its member countries; Afghanistan, Bangladesh, Bhutan, Nepal, India, Maldives, Pakistan, and Sri Lanka. In summary, reactive nitrogen (Nr) in fertilisers is essential for meeting global food and animal feed demands, but Nr pollution has become a major environmental issue across all scales. For SAR, inefficient use of synthetic N fertiliser is a key factor contributing to water pollution, air pollution, climate change, biodiversity loss and soil degradation. Further insights are provided on major fertiliser products, as well as in crop production, import and export. These data are essential for informing and promoting sustainable nitrogen management. Evidence based policy is more important than ever. The SANH is supported by UK Research and Innovation (UKRI) through its Global Challenge Research Fund (GCRF) to gather evidence on nitrogen issues to support countries in the South Asian Region (SAR) comprising eight countries (Nepal, Bangladesh, Pakistan, India, Bhutan, Sri Lanka, Afghanistan, and Maldives) to identify solutions and reduce nitrogen waste. SANH is pioneering a UK-SAR research partnership to catalyse transformational change in SAR to tackle the nitrogen challenge, benefi ting the economy, people’s health and the environment. SANH brings together 32 leading research organisations with governments and other partners. This policy brief provides key insights into national fertiliser trends for all eight SAR countries

Evolving MRSA : high-level β-lactam resistance in Staphylococcus aureus is associated with RNA Polymerase alterations and fine tuning of gene expression

Most clinical MRSA (methicillin-resistant S. aureus) isolates exhibit low-level β-lactam resistance (oxacillin MIC 2–4 μg/ml) due to the acquisition of a novel penicillin binding protein (PBP2A), encoded by mecA. However, strains can evolve high-level resistance (oxacillin MIC ≥256 μg/ml) by an unknown mechanism. Here we have developed a robust system to explore the basis of the evolution of high-level resistance by inserting mecA into the chromosome of the methicillin-sensitive S. aureus SH1000. Low-level mecA-dependent oxacillin resistance was associated with increased expression of anaerobic respiratory and fermentative genes. High-level resistant derivatives had acquired mutations in either rpoB (RNA polymerase subunit β) or rpoC (RNA polymerase subunit β’) and these mutations were shown to be responsible for the observed resistance phenotype. Analysis of rpoB and rpoC mutants revealed decreased growth rates in the absence of antibiotic, and alterations to, transcription elongation. The rpoB and rpoC mutations resulted in decreased expression to parental levels, of anaerobic respiratory and fermentative genes and specific upregulation of 11 genes including mecA. There was however no direct correlation between resistance and the amount of PBP2A. A mutational analysis of the differentially expressed genes revealed that a member of the S. aureus Type VII secretion system is required for high level resistance. Interestingly, the genomes of two of the high level resistant evolved strains also contained missense mutations in this same locus. Finally, the set of genetically matched strains revealed that high level antibiotic resistance does not incur a significant fitness cost during pathogenesis. Our analysis demonstrates the complex interplay between antibiotic resistance mechanisms and core cell physiology, providing new insight into how such important resistance properties evolve

Utility of diffusion MRI characteristics of cervical lymph nodes as disease classifier between patients with head and neck squamous cell carcinoma and healthy volunteers

Diffusion MRI characteristics assessed by apparent diffusion coefficient (ADC) histogram analysis in head and neck squamous cell carcinoma (HNSCC) have been reported as helpful in classifying tumours based on diffusion characteristics. There is little reported on HNSCC lymph nodes classification by diffusion characteristics. The aim of this study was to determine whether pretreatment nodal microstructural diffusion MRI characteristics can classify diseased nodes of patients with HNSCC from normal nodes of healthy volunteers. Seventy-nine patients with histologically confirmed HNSCC prior to chemoradiotherapy, and eight healthy volunteers, underwent diffusion-weighted (DW) MRI at a 1.5-T MR scanner. Two radiologists contoured lymph nodes on DW (b = 300 s/m2) images. ADC, distributed diffusion coefficient (DDC) and alpha (α) values were calculated by monoexponential and stretched exponential models. Histogram analysis metrics of drawn volume were compared between patients and volunteers using a Mann–Whitney test. The classification performance of each metric between the normal and diseased nodes was determined by receiver operating characteristic (ROC) analysis. Intraclass correlation coefficients determined interobserver reproducibility of each metric based on differently drawn ROIs by two radiologists. Sixty cancerous and 40 normal nodes were analysed. ADC histogram analysis revealed significant differences between patients and volunteers (p ≤0.0001 to 0.0046), presenting ADC distributions that were more skewed (1.49 for patients, 1.03 for volunteers; p = 0.0114) and ‘peaked’ (6.82 for patients, 4.20 for volunteers; p = 0.0021) in patients. Maximum ADC values exhibited the highest area under the curve ([AUC] 0.892). Significant differences were revealed between patients and volunteers for DDC and α value histogram metrics (p ≤0.0001 to 0.0044); the highest AUC were exhibited by maximum DDC (0.772) and the 25th percentile α value (0.761). Interobserver repeatability was excellent for mean ADC (ICC = 0.88) and the 25th percentile α value (ICC = 0.78), but poor for all other metrics. These results suggest that pretreatment microstructural diffusion MRI characteristics in lymph nodes, assessed by ADC and α value histogram analysis, can identify nodal disease

Modelling freshwater nitrogen and phosphorus across South Asia

Nitrogen is essential to life and is a vital nutrient for plant growth and food production, however, its natural cycle has been drastically altered by our activities. Nitrogen pollution is a growing threat to our health, ecosystems and freshwater water bodies. South Asia is one of the affected regions with levels of nitrogen pollution rapidly increasing. In this study, a regional-scale model of freshwater flow and macronutrients (N and P) has been developed for the whole of South Asia. The freshwater model of water quantity (flow) and water quality is based on an existing grid-based model formulation HMF-WA (Hydrological Modelling-Framework for West Africa: Rameshwaran et al. (2021)), coupled with a nutrient-routing approach developed for long-term and large-scale use (LTLS: Bell et al. (2021)). The model combines grid-based runoff-production schemes with a Kinematic Wave (KW) flow routing approach in order to estimate river flows and nutrient fluxes on a regular grid across the region. The model simulates spatially consistent river flows and macronutrient fluxes on a 0.1°×0.1° grid (approximately 10km×10km) continuously across the whole domain. Nutrient inputs to rivers are derived using spatial datasets of land cover and spatiotemporal dominant nutrient sources which are atmospheric deposition, fertiliser application, livestock numbers and human population (Figure 1). Regional scale simulations driven by observed weather data are assessed against observed flows and water quality data before undertaking an analysis of the impact of projected future N scenarios including impacts of technology-based abatement measures and dietary change on pollution

Identification of potential “Remedies” for Air Pollution (nitrogen) Impacts on Designated Sites (RAPIDS)

Atmospheric nitrogen (N) deposition is a significant threat to semi-natural habitats and species in the UK, resulting in on-going erosion of habitat quality and declines in many species of high conservation value. The project focused on impacts and remedies for designated conservation sites, especially Natura 2000 sites protected under the EU Habitats Directive. However, the approach and certainly the measures could be equally applied to other areas of high conservation value. Evidence was drawn together to develop a framework for identifying key N threats at individual sites as a basis to target mitigation options in the context of potential legislative, voluntary and financial instruments

Application of time-dependent density functional theory to optical activity

As part of a general study of the time-dependent local density approximation (TDLDA), we here report calculations of optical activity of chiral molecules. The theory automatically satisfies sum rules and the Kramers-Kronig relation between circular dichroism and optical rotatory power. We find that the theory describes the measured circular dichroism of the lowest states in methyloxirane with an accuracy of about a factor of two. In the chiral fullerene C_76 the TDLDA provides a consistent description of the optical absorption spectrum, the circular dichroism spectrum, and the optical rotatory power, except for an overall shift of the theoretical spectrum.Comment: 17 pages and 13 PostScript figure

Atmospheric ammonia assessments on six designated sites in Northern Ireland. Year 1: June 2020 – May 2021

Report to DAERA NIEA (Project 07102). Atmospheric ammonia (NH3) gas concentrations were monitored on six designated sites of international and national importance (Special Areas of Conservation, SAC and Areas of Special Scientific Interest (ASSI)) across Northern Ireland, to assess threats from atmospheric nitrogen inputs. The monitoring strategy at each designated site aims to capture the high spatial variability of NH3 and any associated atmospheric concentration gradients away from sources, where the highest concentrations (and local sources) may be and where the largest ecosystem impacts are likely to occur. The sites are also part of the cross-border INTERREG Va funded Collaborative Action for the Natura Network (CANN) project (2017-2021), managed by the Special EU Programmes Body. The measurement data will provide supporting evidence to develop site-specific mitigation strategies, if necessary and appropriate. It is hypothesised that boundaries of a designated site that are closest to, and downwind of sources (e.g. intensive livestock units) will be exposed to the highest NH3 concentrations and therefore most at risk from adverse effects on sensitive vegetation. This report presents monthly NH3 measurements from the first year of monitoring, between June 2020 and May 2021

Improving predictive asthma algorithms with modelled environment data for Scotland: an observational cohort study protocol

Introduction Asthma has a considerable, but potentially, avoidable burden on many populations globally. Scotland has some of the poorest health outcomes from asthma. Although ambient pollution, weather changes and sociodemographic factors have been associated with asthma attacks, it remains unclear whether modelled environment data and geospatial information can improve population-based asthma predictive algorithms. We aim to create the afferent loop of a national learning health system for asthma in Scotland. We will investigate the associations between ambient pollution, meteorological, geospatial and sociodemographic factors and asthma attacks.Methods and Analysis We will develop and implement a secured data governance and linkage framework to incorporate primary care health data, modelled environment data, geospatial population and sociodemographic data. Data from 75 recruited primary care practices (n=500 000 patients) in Scotland will be used. Modelled environment data on key air pollutants at a horizontal resolution of 5 km×5 km at hourly time steps will be generated using the EMEP4UK atmospheric chemistry transport modelling system for the datazones of the primary care practices’ populations. Scottish population census and education databases will be incorporated into the linkage framework for analysis. We will then undertake a longitudinal retrospective observational analysis. Asthma outcomes include asthma hospitalisations and oral steroid prescriptions. Using a nested case–control study design, associations between all covariates will be measured using conditional logistic regression to account for the matched design and to identify suitable predictors and potential candidate algorithms for an asthma learning health system in Scotland.Findings from this study will contribute to the development of predictive algorithms for asthma outcomes and be used to form the basis for our learning health system prototype.Ethics and dissemination The study received National Health Service Research Ethics Committee approval (16/SS/0130) and also obtained permissions via the Public Benefit and Privacy Panel for Health and Social Care in Scotland to access, collate and use the following data sets: population and housing census for Scotland; Scottish education data via the Scottish Exchange of Data and primary care data from general practice Data Custodians. Analytic code will be made available in the open source GitHub website. The results of this study will be published in international peer reviewed journals