Stabilising Lyme Regis – a strategic approach

Coastal erosion and landslides have been a constant threat to Lyme Regis in West Dorset, UK for over 250 years. By the 1980s, the frequency and scale of coastal erosion and land instability had reached a point whereby the local council realised that a change from the previous ad hoc repair and protection approach was needed to secure the long-term future of the town. An environmental improvements initiative was developed from then onwards to provide a strategic and integrated programme of coast protection and cliff stabilisation measures designed to mitigate the increasing threat of climate change, coastal erosion and landslides, while respecting the site’s unique heritage and environmental interests. This paper outlines the background and principal phases of the project that have been successfully delivered over the period 1990–2015

Accounting for spatial autocorrelation and environment are important to derive robust bat population trends from citizen science data

Monitoring wildlife populations is essential if global targets to reverse biodiversity declines are to be met. Recent analysis of data from the UK’s long-term National Bat Monitoring Programme (NBMP) suggests stable or increasing population trends for many bat species, and these statistics help inform progress towards national biodiversity targets. However, although based on robust citizen science survey designs, it is unknown how sensitive these trends are to spatial and environmental biases. Here we use Bayesian hierarchical modelling with integrated nested Laplace approximation (INLA), to examine the impact of these types of biases on the population trends using relative occupancy of four species monitored by the NBMP Field Survey in Great Britain (GB): Pipistrellus pipistrellus, P. pygmaeus, Nyctalus noctula and Eptesicus serotinus. Where possible, we also disaggregated trends to national levels using the best model per species to determine if national differences in trends remain once sampling biases are accounted for. Although we found evidence of spatial clustering in the NBMP Field Survey locations, the previously reported GB-wide population trends are broadly robust to spatial autocorrelation. In most species, accounting for spatial autocorrelation and species-environment relationships improved model fit. The nationally disaggregated models highlighted that GB-wide trends mask differences between England and Scotland, consistent with previous analysis of these data, as well as illustrating large gaps in survey effort, especially in Wales. We suggest that although bat population trends were found to be broadly robust to sampling biases present in these data, small differences could propagate over time and this impact is likely to be more severe in less structured citizen science data. Therefore, ensuring trends are robust to sampling biases present in citizen science datasets is critical to effective monitoring of progress towards biodiversity targets, managing populations sustainably, and ultimately a reversal of global declines

Prevalence, patterns, and predictors of patient-reported non-motor outcomes at 30 days after acute stroke: prospective observational hospital cohort study

Background: Adverse non-motor outcomes are common after acute stroke and likely to substantially affect quality of life, yet few studies have comprehensively assessed their prevalence, patterns, and predictors across multiple health domains.// Aims: We aim to identify the prevalence, patterns and the factors associated with non-motor outcomes 30 days after stroke.// Methods: This prospective observational hospital cohort study (Stroke Investigation in North and Central London (SIGNAL) identified patients with acute ischaemic stroke or intracerebral haemorrhage (ICH) admitted to the Hyperacute Stroke Unit (HASU) University College Hospital (UCH), London, between August 1st 2018 and August 31st 2019. We assessed non-motor outcomes (anxiety, depression, fatigue, sleep, participation in social roles and activities, pain, bowel, and bladder function) at 30-day follow-up using the Patient Reported Outcome Measurement Information System-Version 29 (PROMIS-29) scale and Barthel Index scale.// Results: We obtained follow-up data for 605/719 (84.1%) eligible patients (mean age 72.0 years; 48.3% female; 521 with ischaemic stroke, 84 with ICH). Anxiety (57.0%), fatigue (52.7%), bladder dysfunction (50.2%), reduced social participation (49.2%), and pain (47.9%) were the commonest adverse non-motor outcomes. The rates of adverse non-motor outcomes in ≥1, ≥2 and ≥3 domains were 89%, 66.3% and 45.8%, respectively; in adjusted analyses, stroke due to ICH (compared to ischaemic stroke) and admission stroke severity were the strongest and most consistent predictors. There were significant correlations between; bowel dysfunction and bladder dysfunction (κ= 0.908); reduced social participation and bladder dysfunction (κ= 0.844); and anxiety and fatigue (κ= 0.613). We did not identify correlation for other pairs of non-motor domains.// Conclusions: Adverse non-motor outcomes are very common at one month after stroke, affecting nearly 90% of evaluated patients in at least one health domain, about two-thirds in two or more domains, and almost 50% in three or more domains. Stroke due to ICH and admission stroke severity were the strongest and most consistent predictors. Adverse outcomes occur in pairs of domains such as with anxiety and fatigue.Our findings emphasise the importance of a multi-domain approach to effectively identify adverse non-motor outcomes after stroke to inform the development of more holistic patient recovery programs

Data integration for large-scale models of species distributions

With the expansion in the quantity and types of biodiversity data being collected, there is a need to find ways to combine these different sources to provide cohesive summaries of species’ potential and realized distributions in space and time. Recently, model-based data integration has emerged as a means to achieve this by combining datasets in ways that retain the strengths of each. We describe a flexible approach to data integration using point process models, which provide a convenient way to translate across ecological currencies. We highlight recent examples of large-scale ecological models based on data integration and outline the conceptual and technical challenges and opportunities that arise

Who should be prioritized for renal transplantation?: Analysis of key stakeholder preferences using discrete choice experiments

Background Policies for allocating deceased donor kidneys have recently shifted from allocation based on Human Leucocyte Antigen (HLA) tissue matching in the UK and USA. Newer allocation algorithms incorporate waiting time as a primary factor, and in the UK, young adults are also favoured. However, there is little contemporary UK research on the views of stakeholders in the transplant process to inform future allocation policy. This research project aimed to address this issue. Methods Discrete Choice Experiment (DCE) questionnaires were used to establish priorities for kidney transplantation among different stakeholder groups in the UK. Questionnaires were targeted at patients, carers, donors / relatives of deceased donors, and healthcare professionals. Attributes considered included: waiting time; donor-recipient HLA match; whether a recipient had dependents; diseases affecting life expectancy; and diseases affecting quality of life. Results Responses were obtained from 908 patients (including 98 ethnic minorities); 41 carers; 48 donors / relatives of deceased donors; and 113 healthcare professionals. The patient group demonstrated statistically different preferences for every attribute (i.e. significantly different from zero) so implying that changes in given attributes affected preferences, except when prioritizing those with no rather than moderate diseases affecting quality of life. The attributes valued highly related to waiting time, tissue match, prioritizing those with dependents, and prioritizing those with moderate rather than severe diseases affecting life expectancy. Some preferences differed between healthcare professionals and patients, and ethnic minority and non-ethnic minority patients. Only non-ethnic minority patients and healthcare professionals clearly prioritized those with better tissue matches. Conclusions Our econometric results are broadly supportive of the 2006 shift in UK transplant policy which emphasized prioritizing the young and long waiters. However, our findings suggest the need for a further review in the light of observed differences in preferences amongst ethnic minorities, and also because those with dependents may be a further priority.</p

Cryptic Distant Relatives Are Common in Both Isolated and Cosmopolitan Genetic Samples

Although a few hundred single nucleotide polymorphisms (SNPs) suffice to infer close familial relationships, high density genome-wide SNP data make possible the inference of more distant relationships such as 2nd to 9th cousinships. In order to characterize the relationship between genetic similarity and degree of kinship given a timeframe of 100–300 years, we analyzed the sharing of DNA inferred to be identical by descent (IBD) in a subset of individuals from the 23andMe customer database (n = 22,757) and from the Human Genome Diversity Panel (HGDP-CEPH, n = 952). With data from 121 populations, we show that the average amount of DNA shared IBD in most ethnolinguistically-defined populations, for example Native American groups, Finns and Ashkenazi Jews, differs from continentally-defined populations by several orders of magnitude. Via extensive pedigree-based simulations, we determined bounds for predicted degrees of relationship given the amount of genomic IBD sharing in both endogamous and ‘unrelated’ population samples. Using these bounds as a guide, we detected tens of thousands of 2nd to 9th degree cousin pairs within a heterogenous set of 5,000 Europeans. The ubiquity of distant relatives, detected via IBD segments, in both ethnolinguistic populations and in large ‘unrelated’ populations samples has important implications for genetic genealogy, forensics and genotype/phenotype mapping studies

Using Extended Genealogy to Estimate Components of Heritability for 23 Quantitative and Dichotomous Traits

Important knowledge about the determinants of complex human phenotypes can be obtained from the estimation of heritability, the fraction of phenotypic variation in a population that is determined by genetic factors. Here, we make use of extensive phenotype data in Iceland, long-range phased genotypes, and a population-wide genealogical database to examine the heritability of 11 quantitative and 12 dichotomous phenotypes in a sample of 38,167 individuals. Most previous estimates of heritability are derived from family-based approaches such as twin studies, which may be biased upwards by epistatic interactions or shared environment. Our estimates of heritability, based on both closely and distantly related pairs of individuals, are significantly lower than those from previous studies. We examine phenotypic correlations across a range of relationships, from siblings to first cousins, and find that the excess phenotypic correlation in these related individuals is predominantly due to shared environment as opposed to dominance or epistasis. We also develop a new method to jointly estimate narrow-sense heritability and the heritability explained by genotyped SNPs. Unlike existing methods, this approach permits the use of information from both closely and distantly related pairs of individuals, thereby reducing the variance of estimates of heritability explained by genotyped SNPs while preventing upward bias. Our results show that common SNPs explain a larger proportion of the heritability than previously thought, with SNPs present on Illumina 300K genotyping arrays explaining more than half of the heritability for the 23 phenotypes examined in this study. Much of the remaining heritability is likely to be due to rare alleles that are not captured by standard genotyping arrays

Reconstructing Roma History from Genome-Wide Data

The Roma people, living throughout Europe and West Asia, are a diverse population linked by the Romani language and culture. Previous linguistic and genetic studies have suggested that the Roma migrated into Europe from South Asia about 1,000–1,500 years ago. Genetic inferences about Roma history have mostly focused on the Y chromosome and mitochondrial DNA. To explore what additional information can be learned from genome-wide data, we analyzed data from six Roma groups that we genotyped at hundreds of thousands of single nucleotide polymorphisms (SNPs). We estimate that the Roma harbor about 80% West Eurasian ancestry–derived from a combination of European and South Asian sources–and that the date of admixture of South Asian and European ancestry was about 850 years before present. We provide evidence for Eastern Europe being a major source of European ancestry, and North-west India being a major source of the South Asian ancestry in the Roma. By computing allele sharing as a measure of linkage disequilibrium, we estimate that the migration of Roma out of the Indian subcontinent was accompanied by a severe founder event, which appears to have been followed by a major demographic expansion after the arrival in Europe.Országos Tudományos Kutatási Alapprogramok (OTKA K 103983)Országos Tudományos Kutatási Alapprogramok (OTKA 73430)National Science Foundation (U.S.) (HOMINID grant 1032255)National Institutes of Health (U.S.) (grant GM100233

Preliminary investigation of a significant national Cryptosporidium exceedance in the United Kingdom, August 2023 and ongoing

Routine laboratory surveillance has identified an unprecedented and ongoing exceedance of Cryptosporidium spp. across the United Kingdom, notably driven by C. hominis transmission, since 14 August 2023. Information from 477 reported cases in England and Wales, followed up with a standardised exposure questionnaire as of 25 September 2023, identified foreign travel in 250 (54%) of 463 respondents and swimming in 234 (66%) of 353 cases. A significant, common exposure has not yet been identified in first analyses

Reconstructing Native American Population History

The peopling of the Americas has been the subject of extensive genetic, archaeological and linguistic research; however, central questions remain unresolved1–5. One contentious issue is whether the settlement occurred via a single6–8 or multiple streams of migration from Siberia9–15. The pattern of dispersals within the Americas is also poorly understood. To address these questions at higher resolution than was previously possible, we assembled data from 52 Native American and 17 Siberian groups genotyped at 364,470 single nucleotide polymorphisms. We show that Native Americans descend from at least three streams of Asian gene flow. Most descend entirely from a single ancestral population that we call “First American”. However, speakers of Eskimo-Aleut languages from the Arctic inherit almost half their ancestry from a second stream of Asian gene flow, and the Na-Dene-speaking Chipewyan from Canada inherit roughly one-tenth of their ancestry from a third stream. We show that the initial peopling followed a southward expansion facilitated by the coast, with sequential population splits and little gene flow after divergence, especially in South America. A major exception is in Chibchan-speakers on both sides of the Panama Isthmus, who have ancestry from both North and South America