Diagnosis and investigation of suspected haemophagocytic lymphohistiocytosis in adults: 2023 Hyperinflammation and HLH Across Speciality Collaboration (HiHASC) consensus guideline.

Haemophagocytic lymphohistiocytosis (HLH) is a hyperinflammatory syndrome characterised by persistently activated cytotoxic lymphocytes and macrophages, which, if untreated, leads to multiorgan dysfunction and death. HLH should be considered in any acutely unwell patient not responding to treatment as expected, with prompt assessment to look for what we term the three Fs-fever, falling blood counts, and raised ferritin. Worldwide, awareness of HLH and access to expert management remain inequitable. Terminology is not standardised, classification criteria are validated in specific patient groups only, and some guidelines rely on specialised and somewhat inaccessible tests. The consensus guideline described in this Health Policy was produced by a self-nominated working group from the UK network Hyperinflammation and HLH Across Speciality Collaboration (HiHASC), a multidisciplinary group of clinicians experienced in managing people with HLH. Combining literature review and experience gained from looking after patients with HLH, it provides a practical, structured approach for all health-care teams managing adult (>16 years) patients with possible HLH. The focus is on early recognition and diagnosis of HLH and parallel identification of the underlying cause. To ensure wide applicability, the use of inexpensive, readily available tests is prioritised, but the role of specialist investigations and their interpretation is also addressed.

Validation of reaction norm breeding values for robustness in Australian sheep.

BACKGROUND: There can be variation between animals in how stable their genetic merit is across different environments due to genotype-by-environment (G×E) interactions. This variation could be used in breeding programs to select robust genotypes that combine high overall performance with stable genetic ranking across environments. There have been few attempts to validate breeding values for robustness in livestock, although this is a necessary step towards their implementation in selection decisions. The objective of this study was to validate breeding values for the robustness of body weight across different growth environments that were estimated using reaction norm models in sheep data. RESULTS: Using threefold cross-validation for the progeny of 337 sires, the average correlation between single-step breeding values for the reaction norm slope and the realised robustness of progeny across different growth environments was 0.21. The correlation between breeding values for the reaction slope estimated independently in two different datasets linked by common sires was close to the expected correlation based on theory. CONCLUSIONS: Slope estimated breeding values (EBV) obtained using reaction norm models were predictive of the phenotypic robustness of progeny across different environments and were consistent for sires with progeny in two different datasets. Selection based on reaction norm EBV could be used to increase the robustness of a population to environmental variation.

Micro-genetic environmental sensitivity across macro-environments of chickens reared in Burkina Faso and France.

BACKGROUND: Commercial poultry production systems follow a pyramidal structure with a nucleus of purebred animals under controlled conditions at the top and crossbred animals under commercial production conditions at the bottom. Genetic correlations between the same phenotypes on nucleus and production animals can therefore be influenced by differences both in purebred-crossbred genotypes and in genotype-by-environment interactions across the two environments, known as macro-genetic environmental sensitivity (GES). Within each environment, genotype-by-environment interactions can also occur due to so-called micro-GES. Micro-GES causes heritable variation in phenotypes and decreases uniformity. In this study, genetic variances of body weight (BW) and of micro-GES of BW and the impacts of purebred-crossbred differences and macro-environmental differences on micro-GES of BW were estimated. The dataset contained three subpopulations of slow-growing broiler chickens: purebred chickens (PB) reared in France, and crossbred chickens reared in France (FR) under the same conditions as PB or reared in Burkina Faso (BF) under local conditions. The crossbred chickens were offspring of the same dam line and had PB as their sire line. RESULTS: Estimates of heritability of BW and micro-GES of BW were 0.54 (SE of 0.02) and 0.06 (0.01), 0.67 (0.03) and 0.03 (0.01), and 0.68 (0.04) and 0.02 (0.01) for the BF, FR, and PB subpopulations, respectively. Estimates of the genetic correlations for BW between the three subpopulations were moderately positive (0.37 to 0.53) and those for micro-GES were weakly to moderately positive (0.01 to 0.44). CONCLUSIONS: The results show that the heritability of the micro-GES of BW varies with macro-environment, which indicates that responses to selection are expected to differ between macro-environments. The weak to moderate positive genetic correlations between subpopulations indicate that both macro-environmental differences and purebred-crossbred differences can cause re-ranking of sires based on their estimated breeding values for micro-GES of BW. Thus, the sire that produces the most variable progeny in one macro-environment may not be the one that produces the most variable offspring in another. Similarly, the sire that produces the most variable purebred progeny may not produce the most variable crossbred progeny. The results highlight the need for investigating micro-GES for all subpopulations included in the selection scheme, to ensure optimal genetic gain in all subpopulations.

Working collaboratively with an online advisory group of people with learning disabilities in covid-times: carrier pigeons, cats and drones.

While much attention and emphasis have been given to the role and value of advisory groups in social science research, less has been published on the experiences of those involved in such collaborative efforts. This article reflects on the experiences of academics, collaborators and self-advocacy experts who formed an advisory group for a research project focused on people with learning disabilities' experiences of renting their own homes. Our paper describes the collaboration, how it changed because of Covid and because of changing relationships, and what worked well and what was challenging. This is in part because these more transparent accounts of working together are sometimes missing from research. We discuss issues relating to bureaucratic research systems which are largely inaccessible to people with learning disabilities and how we approached these. We also highlight the joys and benefits of the research approach that we adopted as well as the challenging and more difficult aspects.

This article tells the story of a research project about people with learning disabilities who rent their own homes in England. The article is not so much about the research findings but more about how the research team worked together. This group included self-advocacy experts with learning disabilities, research collaborators and academic researchers. At the start of the project, people with learning disabilities were invited to be part of an advisory group. But as the project went on, this group started to challenge the limits of the role and wanted to be more involved. This changed the course of the research­as well as the fact that it was happening at the same time as the Covid pandemic. The group had some difficult issues to deal with including complicated ethics processes, bureaucracy about getting people paid, and disagreements about language and terminology. We had some hard conversations about the words we use in academia and in real life and who gets to do research. We also had lots of fun wearing silly glasses at Christmas and talking about carrier pigeons. In the end we all felt that the way the research was carried out had improved the project overall.

Partitioning the forms of genotype-by-environment interaction in the reaction norm analysis of stability.

KEY MESSAGE: The reaction norm analysis of stability can be enhanced by partitioning the contribution of different types of G × E to the variation in slope. The slope of regression in a reaction norm model, where the performance of a genotype is regressed over an environmental covariable, is often used as a measure of stability of genotype performance. This method could be developed further by partitioning variation in the slope of regression into the two sources of genotype-by-environment interaction (G × E) which cause it: scale-type G × E (heterogeneity of variance) and rank-type G × E (heterogeneity of correlation). Because the two types of G × E have very different properties, separating their effect would enable a clearer understanding of stability. The aim of this paper was to demonstrate two methods which seek to achieve this in reaction norm models. Reaction norm models were fit to yield data from a multi-environment trial in Barley (Hordeum vulgare), with the adjusted mean yield from each environment used as the environmental covariable. Stability estimated from factor-analytic models, which can disentangle the two types of G × E and estimate stability based on rank-type G × E, was used for comparison. Adjusting the reaction norm slope to account for scale-type G × E using a genetic regression more than tripled the correlation with factor-analytic estimates of stability (0.24-0.26 to 0.80-0.85), indicating that it removed variation in the reaction norm slope that originated from scale-type G × E. A standardisation procedure had a more modest increase (055-0.59) but could be useful when curvilinear reaction norms are required. Analyses which use reaction norms to explore the stability of genotypes could gain additional insight into the mechanisms of stability by applying the methods outlined in this study.

Repeatability of an attention bias test for sheep suggests variable influence of state and trait affect on behaviour.

Understanding the effects of repeated testing on behaviour is essential for behavioural tests that are re-applied to the same individuals for research and welfare assessment purposes. Assessing the repeatability of behaviour can also help us understand the influence of persistent traits vs transient states on animal responses during testing. This study examined the repeatability of behavioural responses in an attention bias test developed for sheep as a measure of affective state. Sheep were assessed in the attention bias test three times (n = 81 sheep), with testing occurring at intervals of 1 year then 2 weeks. During testing, individual sheep were exposed to a dog located behind a window for 3 s in a 4 × 4 m arena, then the dog was obscured from view, removed and sheep behaviours were recorded for 180 s. We hypothesised that behaviours in the test would have moderate-high repeatability but that the mean behavioural responses would change over consecutive trials as sheep habituated to the test environment. To estimate repeatability, data were modelled using restricted maximum likelihood linear mixed-effects models, fitting animal ID as a random effect. Vigilance behaviour, defined as having the head at or above shoulder height, was moderately repeatable (r = 0.58). Latency to eat (r = 0.20) and duration spent looking towards the previous location of the dog (attention to the dog wall) (r = 0.08) had low repeatability. Mean latency to eat did not differ significantly between trials (P = 0.2) and mean vigilance behaviour tended to decrease over the trials (P = 0.07). Mean duration of attention to the dog wall significantly decreased across the trials (P < 0.001), while mean zones crossed increased (P < 0.001), as did behaviours directed towards the exit door such as duration in proximity and pawing at the door. Overall, vigilance behaviour was moderately repeatable, suggesting it may have been driven by temperament or personality traits, while attention and feeding behaviours may have been more influenced by transient affective states or other factors, however further research is needed to better tease apart these potential effects. Sheep demonstrated some habituation to the test over consecutive trials. Care should therefore be taken during future application of the test to ensure all animals undergoing attention bias testing have equivalent experience for a valid interpretation of their relative behavioural responses.

Genome-regulated Assembly of a ssRNA Virus May Also Prepare It for Infection.

Many single-stranded, positive-sense RNA viruses regulate assembly of their infectious virions by forming multiple, cognate coat protein (CP)-genome contacts at sites termed Packaging Signals (PSs). We have determined the secondary structures of the bacteriophage MS2 ssRNA genome (gRNA) frozen in defined states using constraints from X-ray synchrotron footprinting (XRF). Comparison of the footprints from phage and transcript confirms the presence of multiple PSs in contact with CP dimers in the former. This is also true for a virus-like particle (VLP) assembled around the gRNA in vitro in the absence of the single-copy Maturation Protein (MP) found in phage. Since PS folds are present at many sites across gRNA transcripts, it appears that this genome has evolved to facilitate this mechanism of assembly regulation. There are striking differences between the gRNA-CP contacts seen in phage and the VLP, suggesting that the latter are inappropriate surrogates for aspects of phage structure/function. Roughly 50% of potential PS sites in the gRNA are not in contact with the protein shell of phage. However, many of these sit adjacent to, albeit not in contact with, PS-binding sites on CP dimers. We hypothesize that these act as PSs transiently during assembly but subsequently dissociate. Combining the XRF data with PS locations from an asymmetric cryo-EM reconstruction suggests that the genome positions of such dissociations are non-random and may facilitate infection. The loss of many PS-CP interactions towards the 3' end of the gRNA would allow this part of the genome to transit more easily through the narrow basal body of the pilus extruding machinery. This is the known first step in phage infection. In addition, each PS-CP dissociation event leaves the protein partner trapped in a non-lowest free-energy conformation. This destabilizes the protein shell which must disassemble during infection, further facilitating this stage of the life-cycle.

Genomic analysis of the slope of the reaction norm for body weight in Australian sheep.

BACKGROUND: Selection of livestock based on their robustness or sensitivity to environmental variation could help improve the efficiency of production systems, particularly in the light of climate change. Genetic variation in robustness arises from genotype-by-environment (G × E) interactions, with genotypes performing differently when animals are raised in contrasted environments. Understanding the nature of this genetic variation is essential to implement strategies to improve robustness. In this study, our aim was to explore the genetics of robustness in Australian sheep to different growth environments using linear reaction norm models (RNM), with post-weaning weight records of 22,513 lambs and 60 k single nucleotide polymorphisms (SNPs). The use of scale-corrected genomic estimated breeding values (GEBV) for the slope to account for scale-type G × E interactions was also investigated. RESULTS: Additive genetic variance was observed for the slope of the RNM, with genetic correlations between low- and high-growth environments indicating substantial re-ranking of genotypes (0.44-0.49). The genetic variance increased from low- to high-growth environments. The heritability of post-weaning body weight ranged from 0.28 to 0.39. The genetic correlation between intercept and slope of the reaction norm for post-weaning body weight was low to moderate when based on the estimated (co)variance components but was much higher when based on back-solved SNP effects. An initial analysis suggested that a region on chromosome 11 affected both the intercept and the slope, but when the GEBV for the slope were conditioned on the GEBV for the intercept to remove the effect of scale-type G × E interactions on SNP effects for robustness, a single genomic region on chromosome 7 was found to be associated with robustness. This region included genes previously associated with growth traits and disease susceptibility in livestock. CONCLUSIONS: This study shows a significant genetic variation in the slope of RNM that could be used for selecting for increased robustness of sheep. Both scale-type and rank-type G × E interactions contributed to variation in the slope. The correction for scale effects of GEBV for the slope should be considered when analysing robustness using RNM. Overall, robustness appears to be a highly polygenic trait.

The dying patient: taboo, controversy and missing terms of reference for designers-an architectural perspective.

Contemporary society has grown seemingly detached from the realities of growing old and subsequently, dying. A consequence, perhaps, of death becoming increasingly overmedicalised, nearly one in two UK nationals die institutional deaths. In this article we, two architectural scholars engaged in teaching, research and practice and a nurse and healthcare scholar with a focus on end-of-life care and peoples' experiences, wish to draw attention to a controversy resulting from a paucity in current literature on the terms of reference of the dying 'patient' as we navigate the future implications of the COVID-19 pandemic. This contributes to a relative lack of touchstones for architects to refer to when designing person-centred palliative care environments. Unlike common building types, architects are extremely unlikely to have lived experience of palliative care environments as patients; and therefore, require the help of healthcare professionals to imagine and empathise with the requirements of a person dying away from home. This paper includes a review of ageing and dying literature to understand, and distil from an architectural perspective, who, design professionals, are designing for and to remember the nuanced characteristics of those we hold a duty of care toward. We ask readers to heed the importance of accurate terms of reference, especially when commissioning and/or designing environments of palliative care. Furthermore, we put forward an appeal for interdisciplinary collaboration to develop a framework for codesigning positive experiences of person-centred care and environments at the end of life.

In vitro functional analysis of gRNA sites regulating assembly of hepatitis B virus.

The roles of RNA sequence/structure motifs, Packaging Signals (PSs), for regulating assembly of an HBV genome transcript have been investigated in an efficient in vitro assay containing only core protein (Cp) and RNA. Variants of three conserved PSs, within the genome of a strain not used previously, preventing correct presentation of a Cp-recognition loop motif are differentially deleterious for assembly of nucleocapsid-like particles (NCPs). Cryo-electron microscopy reconstruction of the T = 4 NCPs formed with the wild-type gRNA transcript, reveal that the interior of the Cp shell is in contact with lower resolution density, potentially encompassing the arginine-rich protein domains and gRNA. Symmetry relaxation followed by asymmetric reconstruction reveal that such contacts are made at every symmetry axis. We infer from their regulation of assembly that some of these contacts would involve gRNA PSs, and confirmed this by X-ray RNA footprinting. Mutation of the ε stem-loop in the gRNA, where polymerase binds in vivo, produces a poor RNA assembly substrate with Cp alone, largely due to alterations in its conformation. The results show that RNA PSs regulate assembly of HBV genomic transcripts in vitro, and therefore may play similar roles in vivo, in concert with other molecular factors.

Evaluation of partial body weight for predicting body weight and average daily gain in growing beef cattle.

Information on body weight and average daily gain (ADG) of growing animals is key not only to monitoring performance, but also for use in genetic evaluations in the pursuit of achieving sustainable genetic gain. Accurate calculation of ADG, however, requires serial measures of body weight over at least 70 days. This can be resource intensive and thus alternative approaches to predicting individual animal ADG warrant investigation. One such approach is the use of continuously collected individual animal partial body weights. The objective of the present study was to determine the utility of partial body weights in predicting both body weight and ADG; a secondary objective was to deduce the appropriate length of test to determine ADG from partial body weight records. The dataset used consisted of partial body weights, predicted body weights and recorded body weights recorded for 8,972 growing cattle from a range of different breed types in 35 contemporary groups. The relationships among partial body weight, predicted body weight and recorded body weight at the beginning and end of the performance test were determined and calculated ADG per animal from each body weight measure were also compared. On average, partial body weight explained 90.7 ± 2.0% of the variation in recorded body weight at the beginning of the postweaning gain test and 87.9 ± 2.9% of the variation in recorded body weight at its end. The GrowSafe proprietary algorithm to predict body weight from the partial body weight strengthened these coefficients of determination to 95.1 ± 0.9% and 94.9 ± 0.8%, respectively. The ADG calculated from the partial body weight or from the predicted body weight were very strongly correlated (r = 0.95); correlations between these ADG values with those calculated from the recorded body weights were weaker at 0.81 and 0.78, respectively. For some applications, ADG may be measured with sufficient accuracy with a test period of 50 days using partial body weights. The intended inference space is to individual trials which have been represented in this study by contemporary groups of growing cattle from different genotypes.

DALES, Drug Allergy Labels in Elective Surgical patients: a prospective, multicentre cross-sectional study of prevalence, nature and anaesthetists' approach to management.

BACKGROUND: We sought to define the prevalence and nature of patient-reported drug allergies, determine their impact on prescribing, and explore drug allergy knowledge and attitudes amongst anaesthetists. METHODS: We performed a prospective cross-sectional study in 213 UK hospitals in 2018. Elective surgical patients were interviewed, with a detailed allergy history taken in those self-reporting drug allergy. Anaesthetists completed a questionnaire concerning perioperative drug allergy. RESULTS: Of 21 219 patients included, 6214 (29.3 %) (95% confidence interval [CI]: 28.7-29.9) reported drug allergy. Antibiotics, NSAIDs, and opioids were the most frequently implicated agents. Of a total of 8755 reactions, 2462 (28.1%) (95% CI: 29.2-31.1) were categorised as high risk for representing genuine allergy after risk stratification. A history suggestive of chronic spontaneous urticaria significantly increased the risk of reporting drug allergy (odds ratio 2.68; 95% CI: 2.4-3; P<0.01). Of 4756 anaesthetists completing the questionnaire, 1473 (31%) (95% CI: 29.7-32.3) routinely discuss perioperative allergy risk with patients. Prescribing habits in the presence of drug allergy labels differ depending on the implicated agent. Most anaesthetists (4678/4697; 99.6%) (95% CI: 99.4-99.8) prescribe opioids when reactions are consistent with side-effects, although 2269/4697 (48%) (95% CI: 46.9-49.7) would avoid the specific opioid reported. CONCLUSIONS: Almost 30% of UK elective surgical patients report a history of drug allergies, but the majority of reported reactions are likely to be non-allergic reactions. Allergy labels can impact on perioperative prescribing through avoidance of important drugs and use of less effective alternatives. We highlight important knowledge gaps about drug allergy amongst anaesthetists, and the need for improved education around allergy.

Evolution of a virus-like architecture and packaging mechanism in a repurposed bacterial protein.

Viruses are ubiquitous pathogens of global impact. Prompted by the hypothesis that their earliest progenitors recruited host proteins for virion formation, we have used stringent laboratory evolution to convert a bacterial enzyme that lacks affinity for nucleic acids into an artificial nucleocapsid that efficiently packages and protects multiple copies of its own encoding messenger RNA. Revealing remarkable convergence on the molecular hallmarks of natural viruses, the accompanying changes reorganized the protein building blocks into an interlaced 240-subunit icosahedral capsid that is impermeable to nucleases, and emergence of a robust RNA stem-loop packaging cassette ensured high encapsidation yields and specificity. In addition to evincing a plausible evolutionary pathway for primordial viruses, these findings highlight practical strategies for developing nonviral carriers for diverse vaccine and delivery applications.

The lexicon of antimicrobial peptides: a complete set of arginine and tryptophan sequences.

Our understanding of the activity of cationic antimicrobial peptides (AMPs) has focused on well-characterized natural sequences, or limited sets of synthetic peptides designed de novo. We have undertaken a comprehensive investigation of the underlying primary structural features that give rise to the development of activity in AMPs. We consider a complete set of all possible peptides, up to 7 residues long, composed of positively charged arginine (R) and / or hydrophobic tryptophan (W), two features most commonly associated with activity. We found the shortest active peptides were 4 or 5 residues in length, and the overall landscapes of activity against gram-positive and gram-negative bacteria and a yeast were positively correlated. For all three organisms we found a single activity peak corresponding to sequences with around 40% R; the presence of adjacent W duplets and triplets also conferred greater activity. The mechanistic basis of these activities comprises a combination of lipid binding, particularly to negatively charged membranes, and additionally peptide aggregation, a mode of action previously uninvestigated for such peptides. The maximum specific antimicrobial activity appeared to occur in peptides of around 10 residues, suggesting 'diminishing returns' for developing larger peptides, when activity is considered per residue of peptide.

Anaesthesia and COVID-19: infection control.

The world is currently facing an unprecedented healthcare crisis caused by a pandemic novel beta coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The pathogen is spread by human-to-human transmission via droplets exposure and contact transfer, causing mild symptoms in the majority of cases, but critical illness, bilateral viral pneumonia, and acute respiratory distress syndrome (ARDS) in a minority. Currently, controlling infection to prevent the spread of SARS-CoV-2 is the primary public healthcare intervention used. The pace of transmission and global scale of SARS-CoV-2 infections has implications for strategic oversight, resource management, and responsiveness in infection control. This article presents a summary of learning points in epidemiological infection control from the SARS epidemic, alongside a review of evidence connecting current understanding of the virologic and environmental contamination properties of SARS-CoV-2. We present suggestions for how personal protective equipment policies relate to the viral pandemic context and how the risk of transmission by and to anaesthetists, intensivists, and other healthcare workers can be minimised.

The Impact of Genomic and Traditional Selection on the Contribution of Mutational Variance to Long-Term Selection Response and Genetic Variance.

De novo mutations (DNM) create new genetic variance and are an important driver for long-term selection response. We hypothesized that genomic selection exploits mutational variance less than traditional selection methods such as mass selection or selection on pedigree-based breeding values, because DNM in selection candidates are not captured when the selection candidates' own phenotype is not used in genomic selection, DNM are not on SNP chips and DNM are not in linkage disequilibrium with the SNP on the chip. We tested this hypothesis with Monte Carlo simulation. From whole-genome sequence data, a subset of ∼300,000 variants was used that served as putative markers, quantitative trait loci or DNM. We simulated 20 generations with truncation selection based on breeding values from genomic best linear unbiased prediction without (GBLUP_no_OP) or with own phenotype (GBLUP_OP), pedigree-based BLUP without (BLUP_no_OP) or with own phenotype (BLUP_OP), or directly on phenotype. GBLUP_OP was the best strategy in exploiting mutational variance, while GBLUP_no_OP and BLUP_no_OP were the worst in exploiting mutational variance. The crucial element is that GBLUP_no_OP and BLUP_no_OP puts no selection pressure on DNM in selection candidates. Genetic variance decreased faster with GBLUP_no_OP and GBLUP_OP than with BLUP_no_OP, BLUP_OP or mass selection. The distribution of mutational effects, mutational variance, number of DNM per individual and nonadditivity had a large impact on mutational selection response and mutational genetic variance, but not on ranking of selection strategies. We advocate that more sustainable genomic selection strategies are required to optimize long-term selection response and to maintain genetic diversity.

Effect of selection and selective genotyping for creation of reference on bias and accuracy of genomic prediction.

Reference populations for genomic selection usually involve selected individuals, which may result in biased prediction of estimated genomic breeding values (GEBV). In a simulation study, bias and accuracy of GEBV were explored for various genetic models with individuals selectively genotyped in a typical nucleus breeding program. We compared the performance of three existing methods, that is, Best Linear Unbiased Prediction of breeding values using pedigree-based relationships (PBLUP), genomic relationships for genotyped animals only (GBLUP) and a Single-Step approach (SSGBLUP) using both. For a scenario with no-selection and random mating (RR), prediction was unbiased. However, lower accuracy and bias were observed for scenarios with selection and random mating (SR) or selection and positive assortative mating (SA). As expected, bias disappeared when all individuals were genotyped and used in GBLUP. SSGBLUP showed higher accuracy compared to GBLUP, and bias of prediction was negligible with SR. However, PBLUP and SSGBLUP still showed bias in SA due to high inbreeding. SSGBLUP and PBLUP were unbiased provided that inbreeding was accounted for in the relationship matrices. Selective genotyping based on extreme phenotypic contrasts increased the prediction accuracy, but prediction was biased when using GBLUP. SSGBLUP could correct the biasedness while gaining higher accuracy than GBLUP. In a typical animal breeding program, where it is too expensive to genotype all animals, it would be appropriate to genotype phenotypically contrasting selection candidates and use a Single-Step approach to obtain accurate and unbiased prediction of GEBV.

Passive, continuous monitoring of carbon dioxide geostorage using muon tomography.

Carbon capture and storage is a transition technology from a past and present fuelled by coal, oil and gas and a planned future dominated by renewable energy sources. The technology involves the capture of carbon dioxide emissions from fossil fuel power stations and other point sources, compression of the CO2 into a fluid, transporting it and injecting it deep beneath the Earth's surface into depleted petroleum reservoirs and other porous formations. Once injected, the CO2 must be monitored to ensure that it is emplaced and assimilated as planned and that none leaks back to surface. A variety of methods have been deployed to monitor the CO2 storage site and many such methods have been adapted from oilfield practice. However, such methods are commonly indirect, episodic, require active signal generation and remain expensive throughout the monitoring period that may last for hundreds of years. A modelling framework was developed to concurrently simulate CO2 geostorage conditions and background cosmic-ray muon tomography, in which the potential was assessed for using variations in muon attenuation, due to changes in CO2 abundance, as a means of CO2 detection. From this, we developed a passive, continuous monitoring method for CO2 storage sites using muon tomography, the tools for which can be deployed during the active drilling phase (development) of the storage site. To do this, it was necessary to develop a muon detector that could be used in the hostile environment (saline, high temperature) of the well bore. A prototype detector has been built and tested at the 1.1 km deep Boulby potash mine on the northeast coast of England, supported by the existing STFC Boulby Underground Laboratory on the site. The detector is now ready to be commercialized.This article is part of the Theo Murphy meeting issue 'Cosmic-ray muography'.

Estimation of genomic prediction accuracy from reference populations with varying degrees of relationship.

Genomic prediction is emerging in a wide range of fields including animal and plant breeding, risk prediction in human precision medicine and forensic. It is desirable to establish a theoretical framework for genomic prediction accuracy when the reference data consists of information sources with varying degrees of relationship to the target individuals. A reference set can contain both close and distant relatives as well as 'unrelated' individuals from the wider population in the genomic prediction. The various sources of information were modeled as different populations with different effective population sizes (Ne). Both the effective number of chromosome segments (Me) and Ne are considered to be a function of the data used for prediction. We validate our theory with analyses of simulated as well as real data, and illustrate that the variation in genomic relationships with the target is a predictor of the information content of the reference set. With a similar amount of data available for each source, we show that close relatives can have a substantially larger effect on genomic prediction accuracy than lesser related individuals. We also illustrate that when prediction relies on closer relatives, there is less improvement in prediction accuracy with an increase in training data or marker panel density. We release software that can estimate the expected prediction accuracy and power when combining different reference sources with various degrees of relationship to the target, which is useful when planning genomic prediction (before or after collecting data) in animal, plant and human genetics.