The data-driven future of high-energy-density physics.

High-energy-density physics is the field of physics concerned with studying matter at extremely high temperatures and densities. Such conditions produce highly nonlinear plasmas, in which several phenomena that can normally be treated independently of one another become strongly coupled. The study of these plasmas is important for our understanding of astrophysics, nuclear fusion and fundamental physics-however, the nonlinearities and strong couplings present in these extreme physical systems makes them very difficult to understand theoretically or to optimize experimentally. Here we argue that machine learning models and data-driven methods are in the process of reshaping our exploration of these extreme systems that have hitherto proved far too nonlinear for human researchers. From a fundamental perspective, our understanding can be improved by the way in which machine learning models can rapidly discover complex interactions in large datasets. From a practical point of view, the newest generation of extreme physics facilities can perform experiments multiple times a second (as opposed to approximately daily), thus moving away from human-based control towards automatic control based on real-time interpretation of diagnostic data and updates of the physics model. To make the most of these emerging opportunities, we suggest proposals for the community in terms of research design, training, best practice and support for synthetic diagnostics and data analysis.

Somatic DNA demethylation generates tissue-specific methylation states and impacts flowering time.

Cytosine methylation is a reversible epigenetic modification of DNA. In plants, removal of cytosine methylation is accomplished by the four members of the DEMETER (DME) family of 5-methylcytosine DNA glycosylases, named DME, DEMETER-LIKE2 (DML2), DML3, and REPRESSOR OF SILENCING1 (ROS1) in Arabidopsis thaliana. Demethylation by DME is critical for seed development, preventing experiments to determine the function of the entire gene family in somatic tissues by mutant analysis. Here, we bypassed the reproductive defects of dme mutants to create somatic quadruple homozygous mutants of the entire DME family. dme; ros1; dml2; and dml3 (drdd) leaves exhibit hypermethylated regions compared with wild-type leaves and rdd triple mutants, indicating functional redundancy among all four demethylases. Targets of demethylation include regions co-targeted by RNA-directed DNA methylation and, surprisingly, CG gene body methylation, indicating dynamic methylation at these less-understood sites. Additionally, many tissue-specific methylation differences are absent in drdd, suggesting a role for active demethylation in generating divergent epigenetic states across wild-type tissues. Furthermore, drdd plants display an early flowering phenotype, which involves 5'-hypermethylation and transcriptional down-regulation of FLOWERING LOCUS C. Active DNA demethylation is therefore required for proper methylation across somatic tissues and defines the epigenetic landscape of intergenic and coding regions.

A comparison of feature selection methodologies and learning algorithms in the development of a DNA methylation-based telomere length estimator.

BACKGROUND: The field of epigenomics holds great promise in understanding and treating disease with advances in machine learning (ML) and artificial intelligence being vitally important in this pursuit. Increasingly, research now utilises DNA methylation measures at cytosine-guanine dinucleotides (CpG) to detect disease and estimate biological traits such as aging. Given the challenge of high dimensionality of DNA methylation data, feature-selection techniques are commonly employed to reduce dimensionality and identify the most important subset of features. In this study, our aim was to test and compare a range of feature-selection methods and ML algorithms in the development of a novel DNA methylation-based telomere length (TL) estimator. We utilised both nested cross-validation and two independent test sets for the comparisons. RESULTS: We found that principal component analysis in advance of elastic net regression led to the overall best performing estimator when evaluated using a nested cross-validation analysis and two independent test cohorts. This approach achieved a correlation between estimated and actual TL of 0.295 (83.4% CI [0.201, 0.384]) on the EXTEND test data set. Contrastingly, the baseline model of elastic net regression with no prior feature reduction stage performed less well in general-suggesting a prior feature-selection stage may have important utility. A previously developed TL estimator, DNAmTL, achieved a correlation of 0.216 (83.4% CI [0.118, 0.310]) on the EXTEND data. Additionally, we observed that different DNA methylation-based TL estimators, which have few common CpGs, are associated with many of the same biological entities. CONCLUSIONS: The variance in performance across tested approaches shows that estimators are sensitive to data set heterogeneity and the development of an optimal DNA methylation-based estimator should benefit from the robust methodological approach used in this study. Moreover, our methodology which utilises a range of feature-selection approaches and ML algorithms could be applied to other biological markers and disease phenotypes, to examine their relationship with DNA methylation and predictive value.

Principles of Epigenetic Homeostasis Shared Between Flowering Plants and Mammals.

In diverse eukaryotes, epigenetic information such as DNA methylation is stably propagated over many cell divisions and generations, and can remain the same over thousands or millions of years. However, this stability is the product of dynamic processes that add and remove DNA methylation by specialized enzymatic pathways. The activities of these dynamic pathways must therefore be finely orchestrated in order to ensure that the DNA methylation landscape is maintained with high fidelity - a concept we term epigenetic homeostasis. In this review, we summarize recent insights into epigenetic homeostasis mechanisms in flowering plants and mammals, highlighting analogous mechanisms that have independently evolved to achieve the same goal of stabilizing the epigenetic landscape.

Intraoperative prediction of postanaesthesia care unit hypotension.

BACKGROUND: Postoperative hypotension is associated with adverse outcomes, but intraoperative prediction of postanaesthesia care unit (PACU) hypotension is not routine in anaesthesiology workflow. Although machine learning models may support clinician prediction of PACU hypotension, clinician acceptance of prediction models is poorly understood. METHODS: We developed a clinically informed gradient boosting machine learning model using preoperative and intraoperative data from 88 446 surgical patients from 2015 to 2019. Nine anaesthesiologists each made 192 predictions of PACU hypotension using a web-based visualisation tool with and without input from the machine learning model. Questionnaires and interviews were analysed using thematic content analysis for model acceptance by anaesthesiologists. RESULTS: The model predicted PACU hypotension in 17 029 patients (area under the receiver operating characteristic [AUROC] 0.82 [95% confidence interval {CI}: 0.81-0.83] and average precision 0.40 [95% CI: 0.38-0.42]). On a random representative subset of 192 cases, anaesthesiologist performance improved from AUROC 0.67 (95% CI: 0.60-0.73) to AUROC 0.74 (95% CI: 0.68-0.79) with model predictions and information on risk factors. Anaesthesiologists perceived more value and expressed trust in the prediction model for prospective planning, informing PACU handoffs, and drawing attention to unexpected cases of PACU hypotension, but they doubted the model when predictions and associated features were not aligned with clinical judgement. Anaesthesiologists expressed interest in patient-specific thresholds for defining and treating postoperative hypotension. CONCLUSIONS: The ability of anaesthesiologists to predict PACU hypotension was improved by exposure to machine learning model predictions. Clinicians acknowledged value and trust in machine learning technology. Increasing familiarity with clinical use of model predictions is needed for effective integration into perioperative workflows.

Integrating student and teacher insights to a school-based alcohol program through co-design.

School-based programs may be more effective when an array of stakeholders, including users, are involved during the relevant stages of program co-creation-specifically during key development stages such as design, implementation and evaluation. How such programs can be operationally co-created and tested is less known and is therefore the purpose of this article. Two sequential co-design phases underpin this study. First, a co-design session with 20 health and physical education (HPE) teachers focussed on reviewing, testing and critically discussing initial prototype online modules for an alcohol education program. Teacher insights were assessed and incorporated, and the updated online modules were tested with secondary school students (n = 120) capturing their experience in a classroom setting. Insights from each group were analysed using thematic analysis. Teachers and students serve important roles in program co-creation. Teachers remain an underutilized stakeholder group whom are however critical in delivering important insights to enhance educational program design. Teachers demanded more relevance to the national curriculum, further alignment with curriculum assessment standards, and age appropriate content. Student feedback focussed largely on realistic content, personalization and gamification elements. This study represents an application of the seven-step co-design process and advances understanding of the 'fuzzy back-end' of the process, namely reflecting on feasibility of integrating teacher and student feedback and ideas. More specifically, how these key-yet distinct-stakeholder groups can be involved, and the merits of their involvement are discussed.

There is much research existing for designing change programs across many contexts. Commonly, involving consumers and other related people in the design of these programs is recommended. However less is known about who to involve in the design of programs, what they can be expected to tell you when involved, and when in the design they should be involved. This study explores these questions when involving teachers and students in the design of a school based online education program. Focussing on alcohol education and moderation strategies, the findings of this study support that different stakeholders contribute their own unique insights, whether based on personal bias or based on the nature of their involvement as stakeholders (e.g. as teachers, as parents, as loyal consumers etc.). Furthermore, this study highlights the need for research to distinguish which recommendations to adopt between students and teachers, in a manner generalizable to other contexts and stakeholder groups. From the findings of the current study, the authors recommend multi-disciplinary teams to contrast and enhance a research teams' perceptions regarding stakeholder insights.

Linking stressful life events and chronic inflammation using suPAR (soluble urokinase plasminogen activator receptor).

Stressful life events have been linked to declining health, and inflammation has been proposed as a physiological mechanism that might explain this association. Using 828 participants from the Dunedin Longitudinal Study, we tested whether people who experienced more stressful life events during adulthood would show elevated systemic inflammation when followed up in midlife, at age 45. We studied three inflammatory biomarkers: C-reactive protein (CRP), interleukin-6 (IL-6), and a newer biomarker, soluble urokinase plasminogen activator receptor (suPAR), which is thought to index systemic chronic inflammation. Stressful life events were not associated with CRP or IL-6. However, people who experienced more stressful life events from age 38 to 44 had elevated suPAR at age 45, and had significantly greater increases in suPAR from baseline to follow-up across the same period. When examining stressful life events across the lifespan, both adverse childhood experiences (ACEs) and adult stressful life events were independently associated with suPAR at age 45. ACEs moderated the association of adult stressful life events and suPAR at age 45-children with more ACEs showed higher suPAR levels after experiencing stressful life events as adults. The results suggest systemic chronic inflammation is one physiological mechanism that could link stressful life events and health, and support the use of suPAR as a useful biomarker for such research.

Overcoming Systemic Barriers Preventing Healthy Urban Development in the UK: Main Findings from Interviewing Senior Decision-Makers During a 3-Year Planetary Health Pilot.

This paper sets out the main findings from two rounds of interviews with senior representatives from the UK's urban development industry: the third and final phase of a 3-year pilot, Moving Health Upstream in Urban Development' (UPSTREAM). The project had two primary aims: firstly, to attempt to value economically the health cost-benefits associated with the quality of urban environments and, secondly, to interview those in control of urban development in the UK in order to reveal the potential barriers to, and opportunities for, the creation of healthy urban environments, including their views on the use of economic valuation of (planetary) health outcomes. Much is known about the 'downstream' impact of urban environments on human and planetary health and about how to design and plan healthy towns and cities ('midstream'), but we understand relatively little about how health can be factored in at key governance tipping points further 'upstream', particularly within dominant private sector areas of control (e.g. land, finance, delivery) at sub-national level. Our findings suggest that both public and private sector appeared well aware of the major health challenges posed by poor-quality urban environments. Yet they also recognized that health is not factored adequately into the urban planning process, and there was considerable support for greater use of non-market economic valuation to help improve decision-making. There was no silver bullet however: 110 barriers and 76 opportunities were identified across a highly complex range of systems, actors and processes, including many possible points of targeted intervention for economic valuation. Eight main themes were identified as key areas for discussion and future focus. This findings paper is the second of two on this phase of the project: the first sets out the rationale, approach and methodological lessons learned.

The Application of 'Elite Interviewing' Methodology in Transdisciplinary Research: a Record of Process and Lessons Learned during a 3-Year Pilot in Urban Planetary Health Research.

This paper sets out the rationale and process for the interviewing methodology utilized during a 3-year research pilot, 'Moving Health Upstream in Urban Development' (UPSTREAM). The project had two primary aims: firstly, to attempt to value economically the health cost benefits associated with the quality of urban environments and secondly, to engage with those in control of urban development in the UK in order to determine what are the barriers to and opportunities for creating healthy urban environments, including those identified through the utilisation of economic valuation. Engagement at senior level with those who have most control over key facets of planning and development implementation-such as land disposal, investment, development delivery and planning permission-was central to the approach, which encompassed the adoption of 'elite interviewing', a method developed in the USA in the 1950s and used in the political sciences but relatively unutilized in the health and environmental sciences [1]. Two rounds of semi-structured interviews were undertaken with 15 senior decision-makers from the UK's main urban development delivery agencies, both public and private. The 'elite interviewing' approach successfully enabled the UPSTREAM project to capture and analyse the information received from the interviewees, all of whom held influential or leadership posts in organisations that are important actors in the process of planning, developing and constructing the built environment in the UK. Having academic and practitioner research leads on an equal footing created some minor tensions, but it also appeared to strengthen the rigor of the approach through a broad knowledge of context 'in-house'. This form of co-production at times challenged academic traditions in qualitative analysis, but it also appeared to build trust with interviewees and provided greater clarity of the real-world context under investigation. Findings from this study are written up in a separate paper.

Ancient duons may underpin spatial patterning of gene expression in C4 leaves.

If the highly efficient C4 photosynthesis pathway could be transferred to crops with the C3 pathway there could be yield gains of up to 50%. It has been proposed that the multiple metabolic and developmental modifications associated with C4 photosynthesis are underpinned by relatively few master regulators that have allowed the evolution of C4 photosynthesis more than 60 times in flowering plants. Here we identify a component of one such regulator that consists of a pair of cis-elements located in coding sequence of multiple genes that are preferentially expressed in bundle sheath cells of C4 leaves. These motifs represent duons as they play a dual role in coding for amino acids as well as controlling the spatial patterning of gene expression associated with the C4 leaf. They act to repress transcription of C4 photosynthesis genes in mesophyll cells. These duons are also present in the C3 model Arabidopsis thaliana, and, in fact, are conserved in all land plants and even some algae that use C3 photosynthesis. C4 photosynthesis therefore appears to have coopted an ancient regulatory code to generate the spatial patterning of gene expression that is a hallmark of C4 photosynthesis. This intragenic transcriptional regulatory sequence could be exploited in the engineering of efficient photosynthesis of crops.

Early developmental arrest and impaired gastrointestinal homeostasis in U12-dependent splicing-defective Rnpc3-deficient mice.

Splicing is an essential step in eukaryotic gene expression. While the majority of introns is excised by the U2-dependent, or major class, spliceosome, the appropriate expression of a very small subset of genes depends on U12-dependent, or minor class, splicing. The U11/U12 65K protein (hereafter 65K), encoded by RNPC3, is one of seven proteins that are unique to the U12-dependent spliceosome, and previous studies including our own have established that it plays a role in plant and vertebrate development. To pinpoint the impact of 65K loss during mammalian development and in adulthood, we generated germline and conditional Rnpc3-deficient mice. Homozygous Rnpc3-/- embryos died prior to blastocyst implantation, whereas Rnpc3+/- mice were born at the expected frequency, achieved sexual maturity, and exhibited a completely normal lifespan. Systemic recombination of conditional Rnpc3 alleles in adult (Rnpc3lox/lox ) mice caused rapid weight loss, leukopenia, and degeneration of the epithelial lining of the entire gastrointestinal tract, the latter due to increased cell death and a reduction in cell proliferation. Accompanying this, we observed a loss of both 65K and the pro-proliferative phospho-ERK1/2 proteins from the stem/progenitor cells at the base of intestinal crypts. RT-PCR analysis of RNA extracted from purified preparations of intestinal epithelial cells with recombined Rnpc3lox alleles revealed increased frequency of U12-type intron retention in all transcripts tested. Our study, using a novel conditional mouse model of Rnpc3 deficiency, establishes that U12-dependent splicing is not only important during development but is indispensable throughout life.

Risk of respiratory hospital admission associated with modelled concentrations of Aspergillus fumigatus from composting facilities in England.

Bioaerosols have been associated with adverse respiratory-related health effects and are emitted in elevated concentrations from composting facilities. We used modelled Aspergillus fumigatus concentrations, a good indicator for bioaerosol emissions, to assess associations with respiratory-related hospital admissions. Mean daily Aspergillus fumigatus concentrations were estimated for each composting site for first full year of permit issue from 2005 onwards to 2014 for Census Output Areas (COAs) within 4 km of 76 composting facilities in England, as previously described (Williams et al., 2019). We fitted a hierarchical generalized mixed model to examine the risk of hospital admission with a primary diagnosis of (i) any respiratory condition, (ii) respiratory infections, (iii) asthma, (iv) COPD, (v) diseases due to organic dust, and (vi) Cystic Fibrosis, in relation to quartiles of Aspergillus fumigatus concentrations. Models included a random intercept for each COA to account for over-dispersion, nested within composting facility, on which a random intercept was fitted to account for clustering of the data, with adjustments for age, sex, ethnicity, deprivation, tobacco sales (smoking proxy) and traffic load (as a proxy for traffic-related air pollution). We included 249,748 respiratory-related and 3163 Cystic Fibrosis hospital admissions in 9606 COAs with a population-weighted centroid within 4 km of the 76 included composting facilities. After adjustment for confounders, no statistically significant effect was observed for any respiratory-related (Relative Risk (RR) = 0.99; 95% Confidence Interval (CI) 0.96-1.01) or for Cystic Fibrosis (RR = 1.01; 95% CI 0.56-1.83) hospital admissions for COAs in the highest quartile of exposure. Similar results were observed across all respiratory disease sub-groups. This study does not provide evidence for increased risks of respiratory-related hospitalisations for those living near composting facilities. However, given the limitations in the dispersion modelling, risks cannot be completely ruled out. Hospital admissions represent severe respiratory episodes, so further study would be needed to investigate whether bioaerosols emitted from composting facilities have impacts on less severe episodes or respiratory symptoms.

An Untranslated cis-Element Regulates the Accumulation of Multiple C4 Enzymes in Gynandropsis gynandra Mesophyll Cells.

C4 photosynthesis is a complex phenotype that allows more efficient carbon capture than the ancestral C3 pathway. In leaves of C4 species, hundreds of transcripts increase in abundance compared with C3 relatives and become restricted to mesophyll (M) or bundle sheath (BS) cells. However, no mechanism has been reported that regulates the compartmentation of multiple enzymes in M or BS cells. We examined mechanisms regulating CARBONIC ANHYDRASE4 (CA4) in C4 Gynandropsis gynandra. Increased abundance is directed by both the promoter region and introns of the G. gynandra gene. A nine-nucleotide motif located in the 5' untranslated region (UTR) is required for preferential accumulation of GUS in M cells. This element is present and functional in three additional 5' UTRs and six 3' UTRs where it determines accumulation of two isoforms of CA and pyruvate,orthophosphate dikinase in M cells. Although the GgCA4 5' UTR is sufficient to direct GUS accumulation in M cells, transcripts encoding GUS are abundant in both M and BS. Mutating the GgCA4 5' UTR abolishes enrichment of protein in M cells without affecting transcript abundance. The work identifies a mechanism that directs cell-preferential accumulation of multiple enzymes required for C4 photosynthesis.

The relationship between buildings and health: a systematic review.

BACKGROUND: The built environment exerts one of the strongest directly measurable effects on physical and mental health, yet the evidence base underpinning the design of healthy urban planning is not fully developed. METHOD: This study provides a systematic review of quantitative studies assessing the impact of buildings on health. In total, 7127 studies were identified from a structured search of eight databases combined with manual searching for grey literature. Only quantitative studies conducted between January 2000 and November 2016 were eligible for inclusion. Studies were assessed using the quality assessment tool for quantitative studies. RESULTS: In total, 39 studies were included in this review. Findings showed consistently that housing refurbishment and modifications, provision of adequate heating, improvements to ventilation and water supply were associated with improved respiratory outcomes, quality of life and mental health. Prioritization of housing for vulnerable groups led to improved wellbeing. However, the quality of the underpinning evidence and lack of methodological rigour in most of the studies makes it difficult to draw causal links. CONCLUSION: This review identified evidence to demonstrate the strong association between certain features of housing and wellbeing such as adequate heating and ventilation. Our findings highlight the need for strengthening of the evidence base in order for meaningful conclusions to be drawn.

Methylation-sensitive expression of a DNA demethylase gene serves as an epigenetic rheostat.

Genomes must balance active suppression of transposable elements (TEs) with the need to maintain gene expression. In Arabidopsis, euchromatic TEs are targeted by RNA-directed DNA methylation (RdDM). Conversely, active DNA demethylation prevents accumulation of methylation at genes proximal to these TEs. It is unknown how a cellular balance between methylation and demethylation activities is achieved. Here we show that both RdDM and DNA demethylation are highly active at a TE proximal to the major DNA demethylase gene ROS1. Unexpectedly, and in contrast to most other genomic targets, expression of ROS1 is promoted by DNA methylation and antagonized by DNA demethylation. We demonstrate that inducing methylation in the ROS1 proximal region is sufficient to restore ROS1 expression in an RdDM mutant. Additionally, methylation-sensitive expression of ROS1 is conserved in other species, suggesting it is adaptive. We propose that the ROS1 locus functions as an epigenetic rheostat, tuning the level of demethylase activity in response to methylation alterations, thus ensuring epigenomic stability.

Quantification of biological aging in young adults.

Antiaging therapies show promise in model organism research. Translation to humans is needed to address the challenges of an aging global population. Interventions to slow human aging will need to be applied to still-young individuals. However, most human aging research examines older adults, many with chronic disease. As a result, little is known about aging in young humans. We studied aging in 954 young humans, the Dunedin Study birth cohort, tracking multiple biomarkers across three time points spanning their third and fourth decades of life. We developed and validated two methods by which aging can be measured in young adults, one cross-sectional and one longitudinal. Our longitudinal measure allows quantification of the pace of coordinated physiological deterioration across multiple organ systems (e.g., pulmonary, periodontal, cardiovascular, renal, hepatic, and immune function). We applied these methods to assess biological aging in young humans who had not yet developed age-related diseases. Young individuals of the same chronological age varied in their "biological aging" (declining integrity of multiple organ systems). Already, before midlife, individuals who were aging more rapidly were less physically able, showed cognitive decline and brain aging, self-reported worse health, and looked older. Measured biological aging in young adults can be used to identify causes of aging and evaluate rejuvenation therapies.

The British NHS at 75: Past, Contemporary, and Future Challenges.

This article assesses how and why the National Health Service (NHS) has remained at the forefront of British politics and society for 75 years amid significant economic pressures, organizational strain, shifting ideological trends, ongoing reforms, and an unprecedented public health emergency. The postwar "years of consensus" evolved into alleged decline and ostensible neglect during the 1980s, while New Labour sought to rejuvenate this core public service after 1997, featuring investment and often controversial reforms that challenged the party's social democratic values. Amid the New Labour era, NHS powers filtered down to devolved administrations, while from 2008 retrenchment and austerity ensued, fueled by global recession. Austerity eventually subsided, yet from early 2020 the NHS swiftly faced the extreme conditions of the globalized Covid-19 pandemic. The service continues to face challenges regarding its longer-term viability, and this article analyzes this scenario, within the context of the NHS's 75-year historical legacy, its contemporary status, comparative international trends, and likely future evolution.

Neural network analysis of pharyngeal sounds can detect obstructive upper respiratory disease in brachycephalic dogs.

Brachycephalic obstructive airway syndrome (BOAS) is a highly prevalent respiratory disease affecting popular short-faced dog breeds such as Pugs and French bulldogs. BOAS causes significant morbidity, leading to poor exercise tolerance, sleep disorders and a shortened lifespan. Despite its severity, the disease is commonly missed by owners or disregarded by veterinary practitioners. A key clinical sign of BOAS is stertor, a low-frequency snoring sound. In recent years, a functional grading scheme has been introduced to semi-objectively grade BOAS based on the presence of stertor and other abnormal signs. However, correctly grading stertor requires significant experience and adding an objective component would aid accuracy and repeatability. This study proposes a recurrent neural network model to automatically detect and grade stertor in laryngeal electronic stethoscope recordings. The model is developed using a novel dataset of 665 labelled recordings taken from 341 dogs with diverse BOAS clinical signs. Evaluated via nested cross validation, the neural network predicts the presence of clinically significant BOAS with an area under the receiving operating characteristic of 0.85, an operating sensitivity of 71% and a specificity of 86%. The algorithm could enable widespread screening for BOAS to be conducted by both owners and veterinarians, improving treatment and breeding decisions.

Context-dependent multimodal behaviour in a coral reef fish.

Animals are expected to respond flexibly to changing circumstances, with multimodal signalling providing potential plasticity in social interactions. While numerous studies have documented context-dependent behavioural trade-offs in terrestrial species, far less work has considered such decision-making in fish, especially in natural conditions. Coral reef ecosystems host 25% of all known marine species, making them hotbeds of competition and predation. We conducted experiments with wild Ambon damselfish (Pomacentrus amboinensis) to investigate context-dependent responses to a conspecific intruder; specifically, how nest defence is influenced by an elevated predation risk. We found that nest-defending male Ambon damselfish responded aggressively to a conspecific intruder, spending less time sheltering and more time interacting, as well as signalling both visually and acoustically. In the presence of a model predator compared to a model herbivore, males spent less time interacting with the intruder, with a tendency towards reduced investment in visual displays compensated for by an increase in acoustic signalling instead. We therefore provide ecologically valid evidence that the context experienced by an individual can affect its behavioural responses and multimodal displays towards conspecific threats.

Airborne microplastic monitoring: Developing a simplified outdoor sampling approach using pollen monitoring equipment.

A novel, yet simple, airborne microplastic (MP) sampling approach using global pollen monitoring equipment was applied to identify, characterise and quantify outdoor airborne MPs for the first time. Modification of Burkard spore trap tape adhesive provided particle capture and facilitated downstream spectroscopy analysis. 36 polymer types were identified from a total of 21 days sampling using Burkard spore traps at two locations (United Kingdom and South Africa). MPs were detected in 95 % of daily samples. Mean MP particle levels were 2.0 ± 0.9 MP m-3 (11 polymer types) in Hull (U.K.), during March, 2.9 ± 2.0 MP m-3 (16 types) in Hull in July, and 11.0 ± 5.7 MP m-3 (29 types) in Gqeberha, (S.A.) in August 2023. The most abundant polymer type was nylon (Gqeberha). The approach was compared with two passive sampling methods whereby 27 polymer types were identified and of these, 6 types were above the limit of quantification (LOQ), with poly(methacrolein:styrene) (PMA/PS) the most abundant. Irregularly shaped MPs < 100 µm in length were predominant from all sampling approaches. For the first time, airborne MPs were chemically characterised and quantified using volumetric pollen sampling equipment, representing a viable approach for future airborne MP monitoring.