High-throughput characterization of bacterial responses to complex mixtures of chemical pollutants

Our understanding of how microbes respond to micropollutants, such as pesticides, is almost wholly based on single-species responses to individual chemicals. However, in natural environments, microbes experience multiple pollutants simultaneously. Here we perform a matrix of multi-stressor experiments by assaying the growth of model and non-model strains of bacteria in all 255 combinations of 8 chemical stressors (antibiotics, herbicides, fungicides and pesticides). We found that bacterial strains responded in different ways to stressor mixtures, which could not be predicted simply from their phylogenetic relatedness. Increasingly complex chemical mixtures were both more likely to negatively impact bacterial growth in monoculture and more likely to reveal net interactive effects. A mixed co-culture of strains proved more resilient to increasingly complex mixtures and revealed fewer interactions in the growth response. These results show predictability in microbial population responses to chemical stressors and could increase the utility of next-generation eco-toxicological assays.

Down-the-drain pathways for fipronil and imidacloprid applied as spot-on parasiticides to dogs: Estimating aquatic pollution

Fipronil and imidacloprid have been widely detected in UK surface waters in recent years, often at concentrations that ecotoxicological studies have shown can harm aquatic life. Down-the-drain (DTD) passage of pet flea and tick treatments are being implicated as an important source, with many of the UK's 22 million cats and dogs receiving routine, year-round preventative doses containing these parasiticides. The UK Water Industry's 3rd Chemical Investigation Programme (UKWIR CIP3) has confirmed wastewater as a major entry pathway for these chemicals into surface waters, but the routes by which they enter the wastewater system remain unclear. We addressed this knowledge gap by conducting the first quantification of DTD emissions from 98 dogs treated with spot-on ectoparasiticides containing fipronil or imidacloprid, through bathing, bed washing and washing of owners' hands. Both chemicals were detected in 100 % of washoff samples, with bathing accounting for the largest emissions per event (up to 16.8 % of applied imidacloprid and 24.5 % of applied fipronil). Modelled to account for the frequency of emitting activities, owner handwashing was identified as the largest source of DTD emissions from the population overall, with handwash emissions occurring for at least 28 days following product application and an estimated 4.9 % of imidacloprid and 3.1 % of fipronil applied in dog spot-ons passing down-the-drain via this route. The normalised daily per capita emissions for all routes combined were 8.7 μg/person/day for imidacloprid and 2.1 μg/person/day for fipronil, equivalent to 20-40 % of the daily per capita load in wastewater, as estimated from UKWIR CIP3 data. Within the current international regulatory framework adhered to by the UK, the environmental exposure of veterinary medicines intended for use in small companion animals is assumed to be low, and DTD pathways are not considered. We recommend a systematic review of regulations and practices to address this overlooked pollution pathway.

Regional impacts of warming on biodiversity and biomass in high latitude stream ecosystems across the Northern Hemisphere

Warming can have profound impacts on ecological communities. However, explorations of how differences in biogeography and productivity might reshape the effect of warming have been limited to theoretical or proxy-based approaches: for instance, studies of latitudinal temperature gradients are often conflated with other drivers (e.g., species richness). Here, we overcome these limitations by using local geothermal temperature gradients across multiple high-latitude stream ecosystems. Each suite of streams (6-11 warmed by 1-15°C above ambient) is set within one of five regions (37 streams total); because the heating comes from the bedrock and is not confounded by changes in chemistry, we can isolate the effect of temperature. We found a negative overall relationship between diatom and invertebrate species richness and temperature, but the strength of the relationship varied regionally, declining more strongly in regions with low terrestrial productivity. Total invertebrate biomass increased with temperature in all regions. The latter pattern combined with the former suggests that the increased biomass of tolerant species might compensate for the loss of sensitive species. Our results show that the impact of warming can be dependent on regional conditions, demonstrating that local variation should be included in future climate projections rather than simply assuming universal relationships.

Chronic exposure to environmental temperature attenuates the thermal sensitivity of salmonids

Metabolism, the biological processing of energy and materials, scales predictably with temperature and body size. Temperature effects on metabolism are normally studied via acute exposures, which overlooks the capacity for organisms to moderate their metabolism following chronic exposure to warming. Here, we conduct respirometry assays in situ and after transplanting salmonid fish among different streams to disentangle the effects of chronic and acute thermal exposure. We find a clear temperature dependence of metabolism for the transplants, but not the in-situ assays, indicating that chronic exposure to warming can attenuate salmonid thermal sensitivity. A bioenergetic model accurately captures the presence of fish in warmer streams when accounting for chronic exposure, whereas it incorrectly predicts their local extinction with warming when incorporating the acute temperature dependence of metabolism. This highlights the need to incorporate the potential for thermal acclimation or adaptation when forecasting the consequences of global warming on ecosystems.

Warming indirectly simplifies food webs through effects on apex predators

Warming alters ecosystems through direct physiological effects on organisms and indirect effects via biotic interactions, but their relative impacts in the wild are unknown due to the difficulty in warming natural environments. Here we bridge this gap by embedding manipulative field experiments within a natural stream temperature gradient to test whether warming and apex fish predators have interactive effects on freshwater ecosystems. Fish exerted cascading effects on algal production and microbial decomposition via both green and brown pathways in the food web, but only under warming. Neither temperature nor the presence of fish altered food web structure alone, but connectance and mean trophic level declined as consumer species were lost when both drivers acted together. A mechanistic model indicates that this temperature-induced trophic cascade is determined primarily by altered interactions, which cautions against extrapolating the impacts of warming from reductionist approaches that do not consider the wider food web.

Extra terrestrials: drought creates niche space for rare invertebrates in a large-scale and long-term field experiment

Freshwater habitats are drying more frequently and for longer under the combined pressures of climate change and overabstraction. Unsurprisingly, many aquatic species decline or become locally extinct as their benthic habitat is lost during stream droughts, but less is known about the potential 'winners': those terrestrial species that may exploit emerging niches in drying riverbeds. In particular, we do not know how these transient ecotones will respond as droughts become more extreme in the future. To find out we used a large-scale, long-term mesocosm experiment spanning a wide gradient of drought intensity, from permanent flows to full streambed dewatering, and analysed terrestrial invertebrate community assembly after 1 year. Droughts that caused stream fragmentation gave rise to the most diverse terrestrial invertebrate assemblages, including 10 species with UK conservation designations, and high species turnover between experimental channels. Droughts that caused streambed dewatering produced lower terrestrial invertebrate richness, suggesting that the persistence of instream pools may benefit these taxa as well as aquatic biota. Particularly intense droughts may therefore yield relatively few 'winners' among either aquatic or terrestrial species, indicating that the threat to riverine biodiversity from future drought intensification could be more pervasive than widely acknowledged.

A One-Health environmental risk assessment of contaminants of emerging concern in London's waterways throughout the SARS-CoV-2 pandemic

The SARS-CoV-2 pandemic had huge impacts on global urban populations, activity and health, yet little is known about attendant consequences for urban river ecosystems. We detected significant changes in occurrence and risks from contaminants of emerging concern (CECs) in waterways across Greater London (UK) during the pandemic. We were able to rapidly identify and monitor large numbers of CECs in n = 390 samples across 2019-2021 using novel direct-injection liquid chromatography-mass spectrometry methods for scalable targeted analysis, suspect screening and prioritisation of CEC risks. A total of 10,029 measured environmental concentrations (MECs) were obtained for 66 unique CECs. Pharmaceutical MECs decreased during lockdown in 2020 in the R. Thames (p ≤ 0.001), but then increased significantly in 2021 (p ≤ 0.01). For the tributary rivers, the R. Lee, Beverley Brook, R. Wandle and R. Hogsmill were the most impacted, primarily via wastewater treatment plant effluent and combined sewer overflows. In the R. Hogsmill in particular, pharmaceutical MEC trends were generally correlated with NHS prescription statistics, likely reflecting limited wastewater dilution. Suspect screening of ∼ 1,200 compounds tentatively identified 25 additional CECs at the five most impacted sites, including metabolites such as O-desmethylvenlafaxine, an EU Watch List compound. Lastly, risk quotients (RQs) ≥ 0.1 were calculated for 21 compounds across the whole Greater London freshwater catchment, of which seven were of medium risk (RQ ≥ 1.0) and three were in the high-risk category (RQ ≥ 10), including imidacloprid (RQ = 19.6), azithromycin (15.7) and diclofenac (10.5). This is the largest spatiotemporal dataset of its kind for any major capital city globally and the first for Greater London, representing ∼ 16 % of the population of England, and delivering a foundational One-Health case study in the third largest city in Europe across a global pandemic.

Genomic screening of 16 UK native bat species through conservationist networks uncovers coronaviruses with zoonotic potential

There has been limited characterisation of bat-borne coronaviruses in Europe. Here, we screened for coronaviruses in 48 faecal samples from 16 of the 17 bat species breeding in the UK, collected through a bat rehabilitation and conservationist network. We recovered nine complete genomes, including two novel coronavirus species, across six bat species: four alphacoronaviruses, a MERS-related betacoronavirus, and four closely related sarbecoviruses. We demonstrate that at least one of these sarbecoviruses can bind and use the human ACE2 receptor for infecting human cells, albeit suboptimally. Additionally, the spike proteins of these sarbecoviruses possess an R-A-K-Q motif, which lies only one nucleotide mutation away from a furin cleavage site (FCS) that enhances infectivity in other coronaviruses, including SARS-CoV-2. However, mutating this motif to an FCS does not enable spike cleavage. Overall, while UK sarbecoviruses would require further molecular adaptations to infect humans, their zoonotic risk warrants closer surveillance.

Evaluating the transmission risk of SARS-CoV-2 from sewage pollution

The presence of SARS-CoV-2 in untreated sewage has been confirmed in many countries but its incidence and infection risk in contaminated waters is poorly understood. The River Thames in the UK receives untreated sewage from 57 Combined Sewer Overflows (CSOs), with many discharging dozens of times per year. This study investigated if such discharges provide a pathway for environmental transmission of SARS-CoV-2. Samples of wastewater, surface water, and sediment collected close to six CSOs on the River Thames were assayed over eight months for SARS-CoV-2 RNA and infectious virus. Bivalves were also sampled as an indicator species of viral bioaccumulation. Sediment and water samples from the Danube and Sava rivers in Serbia, where raw sewage is also discharged in high volumes, were assayed as a positive control. No evidence of SARS-CoV-2 RNA or infectious virus was found in UK samples, in contrast to RNA positive samples from Serbia. Furthermore, this study shows that infectious SARS-CoV-2 inoculum is stable in Thames water and sediment for <3 days, while SARS-CoV-2 RNA is detectable for at least seven days. This indicates that dilution of wastewater likely limits environmental transmission, and that detection of viral RNA alone is not an indication of pathogen spillover.

Local stressors mask the effects of warming in freshwater ecosystems

Climate warming is a ubiquitous stressor in freshwater ecosystems, yet its interactive effects with other stressors are poorly understood. We address this knowledge gap by testing the ability of three contrasting null models to predict the joint impacts of warming and a range of other aquatic stressors using a new database of 296 experimental combinations. Despite concerns that stressors will interact to cause synergisms, we found that net impacts were usually best explained by the effect of the stronger stressor alone (the dominance null model), especially if this stressor was a local disturbance associated with human land use. Prediction accuracy depended on stressor identity and how asymmetric stressors were in the magnitude of their effects. These findings suggest we can effectively predict the impacts of multiple stressors by focusing on the stronger stressor, as habitat alteration, nutrients and contamination often override the biological consequences of higher temperatures in freshwater ecosystems.

Predicting catchment suitability for biodiversity at national scales

Biomonitoring of water quality and catchment management are often disconnected, due to mismatching scales. Considerable effort and money are spent each year on routine reach-scale surveying across many sites, particularly in countries like the UK, where nationwide sampling has been conducted using standardised techniques for many decades. Most of these traditional freshwater biomonitoring schemes focus on pre-defined indicators of organic pollution to compare observed vs expected subsets of common macroinvertebrate indicator species. Other taxa, including many threatened species, are often ignored due to their rarity, as are many invasive species, which are seen as undesirable despite becoming increasingly common and widespread in freshwaters, especially in urban ecosystems. Both these types of taxa are often monitored separately for reasons related to biodiversity concerns rather than for gauging water quality. Repurposing such data could therefore provide important new biomonitoring tools that can help catchment managers to directly link the water quality they aim to control with the biodiversity they are trying to protect. Here we used extensive data held in the England Non-Native and Rare/Protected species records that track these two groups of species as a proof-of-concept for linking catchment scale management of freshwater ecosystems and biodiversity to a range of potential drivers across England. We used national land use (Centre for Ecology and Hydrology land cover map) and water quality indicator (Environment Agency water quality data archive) datasets to predict, at the catchment scale, the presence or absence of 48 focal threatened or invasive species of concern routinely sampled by the English Environment Agency, with a median accuracy of 0.81 area under the receiver operating characteristic curve. A variety of water quality indicators and land-use types were useful in predictions, highlighting that future biomonitoring schemes could use such complementary measures to capture a wider spectrum of drivers and responses. In particular, the percentage of a catchment covered by freshwater was the single most important metric, reinforcing the need for space/habitat to support biodiversity, but we were also able to resolve a range of key environmental drivers for particular focal species. We show how our method could inform new catchment management approaches, by highlighting how key relationships can be identified and how to understand, visualise and prioritise catchments that are most suitable for restoration or water quality interventions. The scale of this work, in terms of number of species, drivers and locations, represents a significant step towards forging a new approach to catchment management that enables managers to link drivers they can control (water quality and land use) to the biota they are trying to protect (biodiversity).

Testing bats in rehabilitation for SARS-CoV-2 before release into the wild

Several studies have suggested SARS-CoV-2 originated from a viral ancestor in bats, but whether transmission occurred directly or via an intermediary host to humans remains unknown. Concerns of spillover of SARS-CoV-2 into wild bat populations are hindering bat rehabilitation and conservation efforts in the United Kingdom and elsewhere. Current protocols state that animals cared for by individuals who have tested positive for SARS-CoV-2 cannot be released into the wild and must be isolated to reduce the risk of transmission to wild populations. Here, we propose a reverse transcription-quantitative polymerase chain reaction (RT-qPCR)-based protocol for detection of SARS-CoV-2 in bats, using fecal sampling. Bats from the United Kingdom were tested following suspected exposure to SARS-CoV-2 and tested negative for the virus. With current UK and international legislation, the identification of SARS-CoV-2 infection in wild animals is becoming increasingly important, and protocols such as the one developed here will help improve understanding and mitigation of SARS-CoV-2 in the future.

Metabolic plasticity can amplify ecosystem responses to global warming

Organisms have the capacity to alter their physiological response to warming through acclimation or adaptation, but the consequence of this metabolic plasticity for energy flow through food webs is currently unknown, and a generalisable framework does not exist for modelling its ecosystem-level effects. Here, using temperature-controlled experiments on stream invertebrates from a natural thermal gradient, we show that the ability of organisms to raise their metabolic rate following chronic exposure to warming decreases with increasing body size. Chronic exposure to higher temperatures also increases the acute thermal sensitivity of whole-organismal metabolic rate, independent of body size. A mathematical model parameterised with these findings shows that metabolic plasticity could account for 60% higher ecosystem energy flux with just +2 °C of warming than a traditional model based on ecological metabolic theory. This could explain why long-term warming amplifies ecosystem respiration rates through time in recent mesocosm experiments, and highlights the need to embed metabolic plasticity in predictive models of global warming impacts on ecosystems.

Organisms can alter their physiological response to warming. Here, the authors show that the ability to raise metabolic rate following exposure to warming is inverse to body size and provide a mathematical model which estimates that metabolic plasticity could amplify energy flux through ecosystems in response to warming.

Automated contouring of non-contrast echocardiograms result in similar estimates of left ventricular function to manually contoured contrast-enhanced images in chemotherapy patients

Funding Acknowledgements

Type of funding sources: Private company. Main funding source(s): Ultromics Ltd

Introduction

Transthoracic echocardiography (TTE) assessment of left ventricular (LV) function has a central role in early detection and treatment of cancer-therapy related cardiac dysfunction (CTRCD). Contrast TTE is recommended to aid accurate and reproducible LV contouring , but contrast agents are underused and high variability remains. Using machine learning (ML) to automatically contour the LV reduces variability, and may provide comparable clinical benefit to contrast-enhanced TTE.

Purpose

Retrospective single site study evaluating agreement between LV volumes and function from manually contoured contrast-enhanced TTE and automated contouring of non-contrast enhanced images.

Methods

Adults at risk of developing CTRCD who underwent TTE were recruited. LV volumes (end-diastolic and systolic; EDV and ESV, respectively) and function (ejection fraction; EF) were measured from contrast-enhanced images using manual contouring (MAN-CONT), and non-contrast enhanced images using automation (AUTO-NON). Method comparisons were summarised based on: (i) statistical equivalence (two one-sided t-tests), (ii) systematic difference between methods, via root mean-squared error (RMSE; Deming regression), and (iii) average bias (Bland-Altman). Statistical equivalence bounds were conservatively determined from reproducibility estimates in a similar cohort (EDV, 20 mL; ESV, 15 mL; EF, 5%; REF1), and used to interpret RMSE and bias.

Results

The cohort comprised of patients undergoing treatment for breast cancer, lymphoma, and myeloma. Similar body mass indices were seen between groups (median [IQR]: 26.5 [6.7] kg/m2; Kruskall-Wallace test, p = 0.320), but breast cancer patients were younger (55.0 [14.5], 58.5 [23], 60 [9], respectively; p = 0.034). For estimates of LV volumes and function, statistical equivalence, RMSE, and bias are presented in Table1. Average estimates (mean [SD]) of EDV, ESV, and EF were 121 [33] vs. 112 [33] mL, 50 [23] vs. 44 [19] mL, and 60 [9] vs. 61 [8]%, for MAN-CON and AUTO-NON respectively. Comparing between MAN-CON and AUTO-NON in breast cancer patients, all variables were statistically equivalent (Figure1), and while bias was lower than equivalence bounds, RMSE was only lower for EDV and ESV, not EF. For lymphoma patients, estimates of EDV were statistically equivalent, but not EF and ESV. Bias was lower than equivalence bounds for all variables, whereas RMSE was lower for ESV, but not EDV or EF. For myeloma patients, estimates of ESV and EF were statistically equivalent, but not EDV. While bias was lower than equivalence bounds for all variables, RMSE was not lower for any variable. Conclusions: Estimates of LV function from automated contouring of non-contrast TTE are similar to contrast-enhanced TTE (manually contoured), despite poorer image quality. Automated contouring using ML reduces variability, therefore increasing TTE sensitivity, which is critical when clinical management relies on accurate assessment of LV function. Abstract Table1  Abstract Figure1

Fully automated quantification of LV regional wall motion from echocardiograms to detect myocardial infarction

Funding Acknowledgements

Type of funding sources: Private company. Main funding source(s): Ultromics Ltd

Background

Myocardial wall motion analysis from echocardiography allows precise assessment of cardiac contractile function. Strain, which assesses myocardial deformation, has been shown to enable earlier detection of myocardial disease [1]. Current analysis software packages [2] use semi-automated methods to compute strain, which frequently require manual endocardial delineation and iterative contour adjustment based on tracking results, respectively, causing significant variability.

Purpose

We present a fully automated pipeline for tracking left ventricular (LV) wall motion to quantify global and segmental longitudinal strain from 2D echocardiograms, and go on to validate the pipeline with an openly available myocardial infarction (MI) dataset.

Methods

We applied our existing deep learning-based automated contouring method [3] to delineate the endocardial border in the A4C, A2C and A3C views and combined this with spline-based elastic image registration to track LV motion through time. We sampled points from a region of interest initiated from the endocardial border at the end-diastolic (ED) frame, and tracked subsequent motion by recomputing updated positions of all sample points based on each frame‘s displacement field, enabling us to both track the myocardium throughout the cardiac cycle and calculate longitudinal strain relative to the ED frame. The automated endocardial contour was used to regularise the process. The pipeline was independently tested on the HMC-QU dataset [4] which was downloaded from Kaggle and consists of a single cardiac cycle from the A4C view from 160 patients who were diagnosed with an acute MI and underwent echocardiography either prior to percutaneous coronary intervention or within 24 hours of undergoing the procedure; the dataset includes the labels of ED and end-systolic (ES) frames, as well as the presence of an MI in 6 segments excluding the apical cap (Fig 1a), as determined by the consensus of cardiologists from HMC Hospital in Qatar. The Wilcoxon signed-rank test was used to compare peak strain between the MI and non-MI segments; ROC curves were computed to compare the performance of the automatically derived peak longitudinal strain against the MI labels.

Results

Fig 1b shows ROC curves of peak segmental longitudinal strain for detecting MI, with the best performance in the mid-anterolateral segment (AUC 0.84), and a lower performance for basal segments than mid and apical segments, consistent with known variation in clinical practice [5]. Fig 2 shows that peak longitudinal strain computed from our pipeline was statistically significantly more positive in segments with an MI.

Conclusions

We present a fully automated pipeline for calculating segmental strain across a cardiac cycle to identify infarcted segments without any observer variability. Clinical application of this method has the potential to identify and monitor regional myocardial function and benefit patient management. Abstract Figure. Fig1. ROC of peak longitudinal strains  Abstract Figure. Fig2.Boxplot of peak longitudinal strain

Using Food Webs and Metabolic Theory to Monitor, Model, and Manage Atlantic Salmon—A Keystone Species Under Threat

Populations of Atlantic salmon are crashing across most of its natural range: understanding the underlying causes and predicting these collapses in time to intervene effectively are urgent ecological and socioeconomic priorities. Current management techniques rely on phenomenological analyses of demographic population time-series and thus lack a mechanistic understanding of how and why populations may be declining. New multidisciplinary approaches are thus needed to capitalize on the long-term, large-scale population data that are currently scattered across various repositories in multiple countries, as well as marshaling additional data to understand the constraints on the life cycle and how salmon operate within the wider food web. Here, we explore how we might combine data and theory to develop the mechanistic models that we need to predict and manage responses to future change. Although we focus on Atlantic salmon—given the huge data resources that already exist for this species—the general principles developed here could be applied and extended to many other species and ecosystems.

Fully automated left ventricular ejection fraction and global longitudinal strain predicts obstructive coronary artery disease in patients undergoing stress echocardiography: a multi-centre study

Background

Assessment of LVEF and myocardial deformation with GLS has shown promise in predicting CAD, which may add prognostic information for patients undergoing SE. However, selection bias precludes an accurate assessment of routine clinical SE workflow due to the exclusion of poor image quality and contrast enhanced studies. We hypothesise that an artificial intelligence (AI) pipeline capable of fully automated contouring of the left ventricle and GLS analysis of both non-contrast and contrast SE images is feasible and can predict CAD.

Purpose

The aim of this study was to evaluate the prediction of obstructive coronary artery disease (CAD) from fully automated left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS) measures in a large multicentre population of patients undergoing stress echocardiography (SE).

Methods

500 patients from five medical centres undergoing SE for the clinical evaluation of ischaemic heart disease were included in this study. LVEF and GLS was automatically calculated using AI in non-contrast and contrast images at rest and peak stress. The primary endpoint was CAD assessed using invasive coronary angiography.

Results

Patients with significant CAD demonstrated significantly reduced LVEF and GLS at rest and peak stress (all p&lt;0.001) compared to those without CAD. Of the 130 patients who exhibited myocardial ischaemia at peak stress, patients without significant CAD (37%) had significantly reduced LVEF and GLS when compared to those who did. Multivariate analysis demonstrated that a peak LVEF (0.93; 95% CI 0.9–0.96) and peak GLS (1.15; 95% CI 1.07–1.24) were significant independent predictors of CAD. The addition of automated LVEF and GLS to basic models significantly improved the C statistic from 0.78 to 0.83 and 0.85 (both p&lt;0.001), respectively.

Conclusions

Fully automated LVEF and GLS in non-contrast and contrast SE images is feasible and independently augment the prediction of obstructive CAD above and beyond traditional SE indexes.

Funding Acknowledgement

Type of funding sources: None.

Systematic variation in food web body-size structure linked to external subsidies

The relationship between body mass (M) and size class abundance (N) depicts patterns of community structure and energy flow through food webs. While the general assumption is that M and N scale linearly (on log-log axes), nonlinearity is regularly observed in natural systems, and is theorized to be driven by nonlinear scaling of trophic level (TL) with M resulting in the rapid transfer of energy to consumers in certain size classes. We tested this hypothesis with data from 31 stream food webs. We predicted that allochthonous subsidies higher in the web results in nonlinear M-TL relationships and systematic abundance peaks in macroinvertebrate and fish size classes (latter containing salmonids), that exploit terrestrial plant material and terrestrial invertebrates, respectively. Indeed, both M-N and M-TL significantly deviated from linear relationships and the observed curvature in M-TL scaling was inversely related to that observed in M-N relationships. Systemic peaks in M-N, and troughs in M-TL occurred in size classes dominated by generalist invertebrates, and brown trout. Our study reveals how allochthonous resources entering high in the web systematically shape community size structure and demonstrates the relevance of a generalized metabolic scaling model for understanding patterns of energy transfer in energetically 'open' food webs.

Warming impairs trophic transfer efficiency in a long-term field experiment

In ecosystems, the efficiency of energy transfer from resources to consumers determines the biomass structure of food webs. As a general rule, about 10% of the energy produced in one trophic level makes it up to the next^1-3. Recent theory suggests that this energy transfer could be further constrained if rising temperatures increase metabolic growth costs⁴, although experimental confirmation in whole ecosystems is lacking. Here we quantify nitrogen transfer efficiency-a proxy for overall energy transfer-in freshwater plankton in artificial ponds that have been exposed to seven years of experimental warming. We provide direct experimental evidence that, relative to ambient conditions, 4 °C of warming can decrease trophic transfer efficiency by up to 56%. In addition, the biomass of both phytoplankton and zooplankton was lower in the warmed ponds, which indicates major shifts in energy uptake, transformation and transfer^5,6. These findings reconcile observed warming-driven changes in individual-level growth costs and in carbon-use efficiency across diverse taxa^4,7-10 with increases in the ratio of total respiration to gross primary production at the ecosystem level^11-13. Our results imply that an increasing proportion of the carbon fixed by photosynthesis will be lost to the atmosphere as the planet warms, impairing energy flux through food chains, which will have negative implications for larger consumers and for the functioning of entire ecosystems.

Site-specific automated contouring model generalisibiliy enhancement

Funding Acknowledgements

Type of funding sources: None.

Background

Segmentation of cardiac structures in echocardiography is a pre-requisite for accurately assessing cardiac morphology and function. Manual or semi-automated segmentation are both routinely used in clinical practice, although these can be time-consuming, and can introduce high inter- and intra- operator variability resulting in decreased reproducibility. Effective contouring with no manual input has proven to be challenging due to variations in image quality, image noise, motion during the acquisition and the lack of a well-defined geometry.

Methods

This work proposes a coordinate regression method for automated left ventricle (LV) segmentation, presented in Figure 1 (a). The proposed method is based on a modified U-net architecture that outputs the likelihood of coordinates of landmark points. The obtained likelihood heatmaps are converted to 2D coordinates using a differentiable spatial to numerical transform. The model was trained and validated on UK multisite data (1383 subjects) comprising apical 2 and 4 chamber views for both contrast and non-contrast echocardiographic images.

The Cardiac Acquisitions for Multi-structure Ultrasound Segmentation (CAMUS) echocardiographic image segmentation database was used to assess the performance of the proposed method acting as data from a new clinical site. The CAMUS dataset comprises apical 2 and 4 chamber views acquired from 500 patients with manually annotated cardiac structures for end-diastole and end-systole frames. The original CAMUS dataset was split into training (450 patients) and testing (50 patients), with manual contours being available only for the training dataset. Therefore, we used the CAMUS training dataset to both test and improve our model, by using a random sample of 100 studies as an independent testing dataset and the remaining 350 studies were used for retraining the initial model to improve performance for this dataset.

Results

The results obtained on the testing images are presented in Figure 1 (b). When the model was trained using no CAMUS data for the LV segmentation, a mean Dice coefficient of 0.890 and a median of 0.911 was obtained. Including 350 studies with the original 1383 UK dataset and retraining the same model improved the average Dice coefficient to 0.930 and the median to 0.939. The CAMUS dataset authors reported the best average Dice coefficient of 0.924 on the 50 CAMUS testing images, therefore the proposed points regression method introduces a promising alternative to mask-based segmentation models.

Conclusions

In conclusion, the auto-contouring framework has proven to be effective in terms of its performance and ability to generalise to new data. Furthermore, this work highlights the importance of both evaluating model performance on data from new clinical sites and also enhancing model performance.

Abstract Figure.

Ecological plasticity governs ecosystem services in multilayer networks

Agriculture is under pressure to achieve sustainable development goals for biodiversity and ecosystem services. Services in agro-ecosystems are typically driven by key species, and changes in the community composition and species abundance can have multifaceted effects. Assessment of individual services overlooks co-variance between different, but related, services coupled by a common group of species. This partial view ignores how effects propagate through an ecosystem. We conduct an analysis of 374 agricultural multilayer networks of two related services of weed seed regulation and gastropod mollusc predation delivered by carabid beetles. We found that weed seed regulation increased with the herbivore predation interaction frequency, computed from the network of trophic links between carabids and weed seeds in the herbivore layer. Weed seed regulation and herbivore interaction frequencies declined as the interaction frequencies between carabids and molluscs in the carnivore layer increased. This suggests that carabids can switch to gastropod predation with community change, and that link turnover rewires the herbivore and carnivore network layers affecting seed regulation. Our study reveals that ecosystem services are governed by ecological plasticity in structurally complex, multi-layer networks. Sustainable management therefore needs to go beyond the autecological approaches to ecosystem services that predominate, particularly in agriculture.

Using deep learning to extract novel and quantitative imaging features from perfluoropropane contrast, sulphur hexafluoride contrast and non-contrast stress echocardiography images

Background

Stress echocardiography has become established as the most widely applied non-invasive imaging test for diagnosis of coronary artery disease within the UK. However, stress echocardiography has been substantially qualitative, rather than quantitative, based on visual wall motion assessment. For the first time, we have identified and validated quantitative descriptors of cardiac geometry and motion, extracted from ultrasound images acquired using contrast agents in an automated way.

Purpose

To establish whether these novel imaging features can be generated in an automated, quantifiable and reproducible way from images acquired with perfluoropropane contrast, as well as investigating how these extracted measures compare to those extracted from sulphur hexafluoride contrast and non-contrast studies.

Methods

100 patients who received perfluoropropane contrast during their stress echocardiogram were recruited. Their stress echocardiography images were processed through a deep learning algorithm. Novel feature values were recorded and a subset of 10 studies were repeated. The automated measures of global longitudinal strain (GLS) and ejection fraction (EF) extracted from these images were compared to values previously extracted from sulphur hexafluoride contrast and non-contrast images using the same software.

Results

A full set of 31 novel imaging features were successfully extracted from 79 studies acquired using the perfluoropropane contrast agent with a dropout rate of 14% (n=92, 8 incomplete image sets). Repeated analysis in a subset of 10 perfluoropropane cases demonstrated excellent reproducibility of the extracted feature values (R2=1). Automated values of GLS and EF, at both rest (GLS = −16.4±4.8%, EF = 63±13%) and stress stages (GLS = −17.7±5.8%, EF = 68±11%), were extracted from 83 perfluoropropane studies, with a dropout rate of 16% (n=99, fewer incomplete sets as short axis view not required). The ranges of GLS and EF measures extracted from the perfluoropropane images were comparable to the other contrast studies (n=222) (Rest GLS = −16.8±5.8%, Rest EF = 63±10%; Stress GLS = −19.1±6.7%, Stress EF = 71±9%) and non-contrast studies (n=86) (Rest GLS = −15.7±5.3%, Rest EF = 57±10%; Stress GLS = −17.3±6.4%, Stress EF = 61±14%).

Conclusions

Novel features and clinically relevant measures were extracted from images acquired using perfluoropropane contrast for the first time in a fully automated and reproducible way using a deep learning algorithm. The analysis failure rate and generated measures are comparable to those extracted from images using other commonly used sulphur hexafluoride contrast agents and non-contrast stress echocardiography studies. These findings demonstrate that deep learning algorithms can be used for automated quantitative analysis of stress echocardiograms acquired using various contrast agents and in non-contrast studies to improve stress echocardiography practice.

Funding Acknowledgement

Type of funding source: Private company. Main funding source(s): Lantheus Medical Imaging, Inc.

Fully automated contrast and non-contrast cardiac view detection in echocardiography a multi-centre, multi-vendor study

Background

Correctly identifying views acquired in a 2D echocardiographic examination is paramount to post-processing and quantification steps often performed as part of most clinical workflows. In many exams, particularly in stress echocardiography, microbubble contrast is used which greatly affects the appearance of the cardiac views. Here we present a bespoke, fully automated convolutional neural network (CNN) which identifies apical 2, 3, and 4 chamber, and short axis (SAX) views acquired with and without contrast. The CNN was tested in a completely independent, external dataset with the data acquired in a different country than that used to train the neural network.

Methods

Training data comprised of 2D echocardiograms was taken from 1014 subjects from a prospective multisite, multi-vendor, UK trial with the number of frames in each view greater than 17,500. Prior to view classification model training, images were processed using standard techniques to ensure homogenous and normalised image inputs to the training pipeline. A bespoke CNN was built using the minimum number of convolutional layers required with batch normalisation, and including dropout for reducing overfitting. Before processing, the data was split into 90% for model training (211,958 frames), and 10% used as a validation dataset (23,946 frames). Image frames from different subjects were separated out entirely amongst the training and validation datasets. Further, a separate trial dataset of 240 studies acquired in the USA was used as an independent test dataset (39,401 frames).

Results

Figure 1 shows the confusion matrices for both validation data (left) and independent test data (right), with an overall accuracy of 96% and 95% for the validation and test datasets respectively. The accuracy for the non-contrast cardiac views of &gt;99% exceeds that seen in other works. The combined datasets included images acquired across ultrasound manufacturers and models from 12 clinical sites.

Conclusion

We have developed a CNN capable of automatically accurately identifying all relevant cardiac views used in “real world” echo exams, including views acquired with contrast. Use of the CNN in a routine clinical workflow could improve efficiency of quantification steps performed after image acquisition. This was tested on an independent dataset acquired in a different country to that used to train the model and was found to perform similarly thus indicating the generalisability of the model.

Figure 1. Confusion matrices

Funding Acknowledgement

Type of funding source: Private company. Main funding source(s): Ultromics Ltd.

Consistent temperature dependence of functional response parameters and their use in predicting population abundance

Global warming is one of the greatest threats to the persistence of populations: increased metabolic demands should strengthen pairwise species interactions, which could destabilize food webs at the higher organizational levels. Quantifying the temperature dependence of consumer-resource interactions is thus essential for predicting ecological responses to warming. We explored feeding interactions between different predator-prey pairs in controlled-temperature chambers and in a system of naturally heated streams. We found consistent temperature dependence of attack rates across experimental settings, though the magnitude and activation energy of attack rate were specific to each predator, which varied in mobility and foraging mode. We used these parameters along with metabolic rate measurements to estimate energetic efficiency and population abundance with warming. Energetic efficiency accurately estimated field abundance of a mobile predator that struggled to meet its metabolic demands, but was a poor predictor for a sedentary predator that operated well below its energetic limits. Temperature effects on population abundance may thus be strongly dependent on whether organisms are regulated by their own energy intake or interspecific interactions. Given the widespread use of functional response parameters in ecological modelling, reconciling outcomes from laboratory and field studies increases the confidence and precision with which we can predict warming impacts on natural systems.

Precipitation and temperature drive continental-scale patterns in stream invertebrate production

Secondary production, the growth of new heterotrophic biomass, is a key process in aquatic and terrestrial ecosystems that has been carefully measured in many flowing water ecosystems. We combine structural equation modeling with the first worldwide dataset on annual secondary production of stream invertebrate communities to reveal core pathways linking air temperature and precipitation to secondary production. In the United States, where the most extensive set of secondary production estimates and covariate data were available, we show that precipitation-mediated, low-stream flow events have a strong negative effect on secondary production. At larger scales (United States, Europe, Central America, and Pacific), we demonstrate the significance of a positive two-step pathway from air to water temperature to increasing secondary production. Our results provide insights into the potential effects of climate change on secondary production and demonstrate a modeling framework that can be applied across ecosystems.

Global patterns and drivers of ecosystem functioning in rivers and riparian zones

River ecosystems receive and process vast quantities of terrestrial organic carbon, the fate of which depends strongly on microbial activity. Variation in and controls of processing rates, however, are poorly characterized at the global scale. In response, we used a peer-sourced research network and a highly standardized carbon processing assay to conduct a global-scale field experiment in greater than 1000 river and riparian sites. We found that Earth's biomes have distinct carbon processing signatures. Slow processing is evident across latitudes, whereas rapid rates are restricted to lower latitudes. Both the mean rate and variability decline with latitude, suggesting temperature constraints toward the poles and greater roles for other environmental drivers (e.g., nutrient loading) toward the equator. These results and data set the stage for unprecedented "next-generation biomonitoring" by establishing baselines to help quantify environmental impacts to the functioning of ecosystems at a global scale.

Extreme drought pushes stream invertebrate communities over functional thresholds

Functional traits are increasingly being used to predict extinction risks and range shifts under long-term climate change scenarios, but have rarely been used to study vulnerability to extreme climatic events, such as supraseasonal droughts. In streams, drought intensification can cross thresholds of habitat loss, where marginal changes in environmental conditions trigger disproportionate biotic responses. However, these thresholds have been studied only from a structural perspective, and the existence of functional nonlinearity remains unknown. We explored trends in invertebrate community functional traits along a gradient of drought intensity, simulated over 18 months, using mesocosms analogous to lowland headwater streams. We modelled the responses of 16 traits based on a priori predictions of trait filtering by drought, and also examined the responses of trait profile groups (TPGs) identified via hierarchical cluster analysis. As responses to drought intensification were both linear and nonlinear, generalized additive models (GAMs) were chosen to model response curves, with the slopes of fitted splines used to detect functional thresholds during drought. Drought triggered significant responses in 12 (75%) of the a priori-selected traits. Behavioural traits describing movement (dispersal, locomotion) and diet were sensitive to moderate-intensity drought, as channels fragmented into isolated pools. By comparison, morphological and physiological traits showed little response until surface water was lost, at which point we observed sudden shifts in body size, respiration mode and thermal tolerance. Responses varied widely among TPGs, ranging from population collapses of non-aerial dispersers as channels fragmented to irruptions of small, eurythermic dietary generalists upon extreme dewatering. Our study demonstrates for the first time that relatively small changes in drought intensity can trigger disproportionately large functional shifts in stream communities, suggesting that traits-based approaches could be particularly useful for diagnosing catastrophic ecological responses to global change.

Rapid liquid chromatography tandem mass-spectrometry screening method for urinary metabolites of primary hyperoxaluria

Background

The primary hyperoxalurias are inherited disorders of glyoxylate metabolism that lead to overproduction of oxalate, urolithiasis and renal failure. Delays in diagnosis can be costly in terms of preserving renal function. Here we present a rapid liquid chromatography tandem mass-spectrometry screening method for the analysis of metabolites (primary hyperoxaluria metabolites) produced in excess by primary hyperoxaluria patients that include glycolate, glycerate and 2,4-dihydroxyglutarate.

Methods

Assay performance was compared to our existing gas chromatography–mass spectrometry method and clinical utility established by analysis of urine samples from patients with confirmed primary hyperoxalurias (11 PH1, 12 PH2 and 8 PH3) and controls ( n = 12). An additional 67 urine samples from patients with PH3 were used postvalidation to confirm the derived 2,4-dihydroxyglutarate cut-off.

Results

Glycolate, glycerate and 2,4-dihydroxyglutarate showed a mean bias of 3.3, −22.8 and 5.7%, respectively, compared to our previously published gas chromatography–mass spectrometry method. The mean total imprecision for glycolate, glycerate and 2,4-dihydroxyglutarate was shown to be 6.4, 10 and 11%, respectively. Clinical assessment confirmed that mean urinary glycolate, glycerate and 2,4-dihydroxyglutarate excretion were significantly elevated in patients with PH1, PH2 and PH3, respectively. The greatest sensitivity and specificity for PH1, PH2 and PH3 was achieved at cut-offs of 193, 100 and 4.9 μmol/mmol for glycolate, glycerate and 2,4-dihydroxyglutarate, respectively.

Conclusions

A rapid screening method for the identification and differentiation of patients with suspected PH1, PH2 and PH3 is presented that allows focussing of genetic testing, saving time, money and, with earlier treatment, potential preservation of renal function for these patients.

Bending the rules: exploitation of allochthonous resources by a top-predator modifies size-abundance scaling in stream food webs

Body mass-abundance (M-N) allometries provide a key measure of community structure, and deviations from scaling predictions could reveal how cross-ecosystem subsidies alter food webs. For 31 streams across the UK, we tested the hypothesis that linear log-log M-N scaling is shallower than that predicted by allometric scaling theory when top predators have access to allochthonous prey. These streams all contained a common and widespread top predator (brown trout) that regularly feeds on terrestrial prey and, as hypothesised, deviations from predicted scaling increased with its dominance of the fish assemblage. Our study identifies a key beneficiary of cross-ecosystem subsidies at the top of stream food webs and elucidates how these inputs can reshape the size-structure of these 'open' systems.

Arthropods dataset from different genetically modified maize events and associated controls

Arthropods from four genetically modified (GM) maize hybrids (coleopteran resistant, coleopteran and lepidopteran resistant, lepidopteran resistant+herbicide tolerant and coleopteran resistant and herbicide tolerant) and non-GM varieties were sampled during a two-year field assessment. A total number of 363 555 arthropod individuals were collected. This represents the most comprehensive arthropod dataset from GM maize, and together with weed data, is reasonable to determine functional groups of arthropods and interactions between species. Trophic groups identified from both phytophagous and predatory arthropods were previously considered non-target organisms on which possible detrimental effects of Bacillus thuringiensis (Bt) toxins may have been directly (phytophagous species) or indirectly (predators) detected. The high number of individuals and species and their dynamics through the maize growing season can predict that interactions are highly correlational, and can thus be considered a useful tool to assess potential deleterious effects of Bt toxins on non-target organisms, serving to develop biosafety risk hypotheses for invertebrates exposed to GM maize plants.

Comparing species interaction networks along environmental gradients

Knowledge of species composition and their interactions, in the form of interaction networks, is required to understand processes shaping their distribution over time and space. As such, comparing ecological networks along environmental gradients represents a promising new research avenue to understand the organization of life. Variation in the position and intensity of links within networks along environmental gradients may be driven by turnover in species composition, by variation in species abundances and by abiotic influences on species interactions. While investigating changes in species composition has a long tradition, so far only a limited number of studies have examined changes in species interactions between networks, often with differing approaches. Here, we review studies investigating variation in network structures along environmental gradients, highlighting how methodological decisions about standardization can influence their conclusions. Due to their complexity, variation among ecological networks is frequently studied using properties that summarize the distribution or topology of interactions such as number of links, connectance, or modularity. These properties can either be compared directly or using a procedure of standardization. While measures of network structure can be directly related to changes along environmental gradients, standardization is frequently used to facilitate interpretation of variation in network properties by controlling for some co-variables, or via null models. Null models allow comparing the deviation of empirical networks from random expectations and are expected to provide a more mechanistic understanding of the factors shaping ecological networks when they are coupled with functional traits. As an illustration, we compare approaches to quantify the role of trait matching in driving the structure of plant-hummingbird mutualistic networks, i.e. a direct comparison, standardized by null models and hypothesis-based metaweb. Overall, our analysis warns against a comparison of studies that rely on distinct forms of standardization, as they are likely to highlight different signals. Fostering a better understanding of the analytical tools available and the signal they detect will help produce deeper insights into how and why ecological networks vary along environmental gradients.

Effects of genetically modified maize events expressing Cry34Ab1, Cry35Ab1, Cry1F, and CP4 EPSPS proteins on arthropod complex food webs

Four genetically modified (GM) maize (Zea mays L.) hybrids (coleopteran resistant, coleopteran and lepidopteran resistant, lepidopteran resistant and herbicide tolerant, coleopteran and herbicide tolerant) and its non-GM control maize stands were tested to compare the functional diversity of arthropods and to determine whether genetic modifications alter the structure of arthropods food webs. A total number of 399,239 arthropod individuals were used for analyses. The trophic groups' number and the links between them indicated that neither the higher magnitude of Bt toxins (included resistance against insect, and against both insects and glyphosate) nor the extra glyphosate treatment changed the structure of food webs. However, differences in the average trophic links/trophic groups were detected between GM and non-GM food webs for herbivore groups and plants. Also, differences in characteristic path lengths between GM and non-GM food webs for herbivores were observed. Food webs parameterized based on 2-year in-field assessments, and their properties can be considered a useful and simple tool to evaluate the effects of Bt toxins on non-target organisms.