Habitat loss fragments metacommunities, altering the movement of species between previously connected habitat patches. The consequences of habitat loss for ecosystem functioning depend, in part, on ...how these changes in connectivity alter the spatial insurance effects of biodiversity. Spatial insurance is the maintenance of biodiversity and stable ecosystem functioning in changing environments that occurs when species are able to move between local habitat patches in order to track conditions to which they are adapted. Spatial insurance requires a combination of species sorting dynamics, which allow species to disperse to habitats where they are productive, and mass effect dynamics, where dispersal allows species to persist in marginal habitats where environmental conditions do not support growth. Here we use a spatially explicit metacommunity model to show that the relative contribution of species sorting and mass effects to spatial insurance changes with the rate of dispersal. We then simulate different sequences of habitat loss by removing habitat patches based on their betweenness centrality (the degree to which a patch serves as a connection between other patches in the metacommunity). We demonstrate that the sequence of habitat loss has a large, non‐linear impact on diversity, ecosystem functioning and stability. Spatial insurance is lost because habitat fragmentation impedes species sorting, while promoting mass effects and dispersal limitation. We find that species sorting dynamics, and thus spatial insurance, are most robust to the removal of habitat patches with low betweenness centrality. These findings advance our understanding of how habitat connectivity facilitates the maintenance of biodiversity and ecosystem functioning, and may prove useful for the design of habitat networks.
Dispersal and adaptation both allow species to persist in changing environments. Yet, we have limited understanding of how these processes interact to affect species persistence, especially in ...diverse communities where biotic interactions greatly complicate responses to environmental change. Here we use a stochastic metacommunity model to demonstrate how dispersal and adaptation to environmental change independently and interactively contribute to biodiversity maintenance. Dispersal provides spatial insurance, whereby species persist on the landscape by shifting their distributions to track favorable conditions. In contrast, adaptation allows species to persist by allowing for evolutionary rescue. But, when species both adapt and disperse, dispersal and adaptation do not combine positively to affect biodiversity maintenance, even if they do increase the persistence of individual species. This occurs because faster adapting species evolve to hold onto their initial ranges (i.e., monopolization effects), thus impeding slower adapting species from shifting their ranges and thereby causing extinctions. Importantly, these differences in adaptation speed emerge as the result of competition, which alters population sizes and colonization success. By demonstrating how dispersal and adaptation each independently and interactively contribute to the maintenance of biodiversity, we provide a framework that links the theories of spatial insurance, evolutionary rescue, and monopolization. This highlights the expectation that the maintenance of biodiversity in changing environments depends jointly on rates of dispersal and adaptation, and, critically, the interaction between these processes.
Objectives The objective of this study was to determine whether colchicine 0.5 mg/day can reduce the risk of cardiovascular events in patients with clinically stable coronary disease. Background The ...presence of activated neutrophils in culprit atherosclerotic plaques of patients with unstable coronary disease raises the possibility that inhibition of neutrophil function with colchicine may reduce the risk of plaque instability and thereby improve clinical outcomes in patients with stable coronary disease. Methods In a clinical trial with a prospective, randomized, observer-blinded endpoint design, 532 patients with stable coronary disease receiving aspirin and/or clopidogrel (93%) and statins (95%) were randomly assigned colchicine 0.5 mg/day or no colchicine and followed for a median of 3 years. The primary outcome was the composite incidence of acute coronary syndrome, out-of-hospital cardiac arrest, or noncardioembolic ischemic stroke. The primary analysis was by intention-to-treat. Results The primary outcome occurred in 15 of 282 patients (5.3%) who received colchicine and 40 of 250 patients (16.0%) assigned no colchicine (hazard ratio: 0.33; 95% confidence interval CI 0.18 to 0.59; p < 0.001; number needed to treat: 11). In a pre-specified secondary on-treatment analysis that excluded 32 patients (11%) assigned to colchicine who withdrew within 30 days due to intestinal intolerance and a further 7 patients (2%) who did not start treatment, the primary outcome occurred in 4.5% versus 16.0% (hazard ratio: 0.29; 95% CI: 0.15 to 0.56; p < 0.001). Conclusions Colchicine 0.5 mg/day administered in addition to statins and other standard secondary prevention therapies appeared effective for the prevention of cardiovascular events in patients with stable coronary disease.
Injectable biomimetic hydrogels have great potential for use in regenerative medicine as cellular delivery vectors. However, they can suffer from issues relating to hypoxia, including poor cell ...survival, differentiation, and functional integration owing to the lack of an established vascular network. Here we engineer a hybrid myoglobin:peptide hydrogel that can concomitantly deliver stem cells and oxygen to the brain to support engraftment until vascularisation can occur naturally. We show that this hybrid hydrogel can modulate cell fate specification within progenitor cell grafts, resulting in a significant increase in neuronal differentiation. We find that the addition of myoglobin to the hydrogel results in more extensive innervation within the host tissue from the grafted cells, which is essential for neuronal replacement strategies to ensure functional synaptic connectivity. This approach could result in greater functional integration of stem cell-derived grafts for the treatment of neural injuries and diseases affecting the central and peripheral nervous systems.
Lack of knowledge regarding the nature of biochar alkalis has hindered understanding of pH-sensitive biochar-soil interactions. Here we investigate the nature of biochar alkalinity and present a ...cohesive suite of methods for its quantification. Biochars produced from cellulose, corn stover and wood feedstocks had significant low-pKa organic structural (0.03–0.34 meq g−1), other organic (0–0.92 meq g−1), carbonate (0.02–1.5 meq g−1), and other inorganic (0–0.26 meq g−1) alkalinities. All four categories of biochar alkalinity contributed to total biochar alkalinity and are therefore relevant to pH-sensitive soil processes. Total biochar alkalinity was strongly correlated with base cation concentration, but biochar alkalinity was not a simple function of elemental composition, soluble ash, fixed carbon, or volatile matter content. More research is needed to characterize soluble biochar alkalis other than carbonates and to establish predictive relationships among biochar production parameters and the composition of biochar alkalis.
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•We present a suite of methods for quantifying biochar alkalinity in four categories.•Total biochar alkalinity and distribution of alkalis varied widely among biochars.•Base cation concentration was a good predictor of total biochar alkalinity.•Inorganic alkalis comprised >55% of lignocellulosic biochar alkalinity.
The counterintuitive phenomenon of negative linear compressibility (NLC) is a highly desirable but rare property exploitable in the development of artificial muscles, actuators and next-generation ...pressure sensors. In all cases, material performance is directly related to the magnitude of intrinsic NLC response. Here we show the molecular framework material zinc(II) dicyanoaurate(I), ZnAu(CN)(2)(2), exhibits the most extreme and persistent NLC behaviour yet reported: under increasing hydrostatic pressure its crystal structure expands in one direction at a rate that is an order of magnitude greater than both the typical contraction observed for common engineering materials and also the anomalous expansion in established NLC candidates. This extreme behaviour arises from the honeycomb-like structure of ZnAu(CN)(2)(2) coupling volume reduction to uniaxial expansion, and helical Au…Au 'aurophilic' interactions accommodating abnormally large linear strains by functioning as supramolecular springs.
Child stunting has increasingly become the focus of large-scale global health efforts with the inclusion of stunting eradication as one of the Sustainable Development Goals of the United Nations. ...Child sex has been identified as a biological risk factor for stunting, and sex-specific approaches to stunting prevention have been proposed.
This paper examines four pathways, developmental sensitivity, energetics, caretaking and measurement, proposed to contribute to sex differences in linear growth faltering and stunting risk.
Anthropological, public health and clinical literature on sex differences in stunting and the mechanisms contributing to variability across contexts are reviewed.
The direction of sex differences in stunting prevalence varies across countries and between households. Sex differences in growth trajectories and immune function beginning prenatally place boys at greater risk of infection and undernutrition, but these biological differences are interpreted by parents and within household contexts that are shaped by social and cultural norms which, in turn, influence care and feeding practices.
A perspective that incorporates an examination of the social and environmental factors shaping child growth in specific contexts is needed to understand sex-based vulnerability to stunting and to develop context-appropriate interventions.
•Human’s balance ability is predictable using deep neural networks.•C-LSTM provides a better prediction of human balance patterns.•Human’s risk of fall can be characterized based on force-plate time ...series metrics.•Random sampling and architectural simplicity improve neural network performance.
Early and accurate identification of the balance deficits could reduce falls, in particular for older adults, a prone population. Our work investigates deep neural networks’ capacity to identify human balance patterns towards predicting fall-risk. Human balance ability can be characterized based on commonly-used balance metrics, such as those derived from the force-plate time series. We hypothesized that low, moderate, and high risk of falling can be characterized based on balance metrics, derived from the force-plate time series, in conjunction with deep learning algorithms. Further, we predicted that our proposed One-One-One Deep Neural Networks algorithm provides a considerable increase in performance compared to other algorithms. Here, an open source force-plate dataset, which quantified human balance from a wide demographic of human participants (163 females and males aged 18–86) for varied standing conditions (eyes-open firm surface, eyes-closed firm surface, eyes-open foam surface, eyes-closed foam surface) was used. Classification was based on one of the several indicators of fall-risk tied to the fear of falling: the clinically-used Falls Efficacy Scale (FES) assessment. For human fall-risk prediction, the deep learning architecture implemented comprised of: Recurrent Neural Network (RNN), Long-Short Time Memory (LSTM), One Dimensional Convolutional Neural Network (1D-CNN), and a proposed One-One-One Deep Neural Network. Results showed that our One-One-One Deep Neural Networks algorithm outperformed the other aforementioned algorithms and state-of-the-art models on the same dataset. With an accuracy, precision, and sensitivity of 99.9%, 100%, 100%, respectively at the 12th epoch, we found that our proposed One-One-One Deep Neural Network model is the most efficient neural network in predicting human’s fall-risk (based on the FES measure) using the force-plate time series signal. This is a novel methodology for an accurate prediction of human risk of fall.
Although culture-independent techniques have shown that the lungs are not sterile, little is known about the lung microbiome in chronic obstructive pulmonary disease (COPD). We used pyrosequencing of ...16S amplicons to analyze the lung microbiome in two ways: first, using bronchoalveolar lavage (BAL) to sample the distal bronchi and air-spaces; and second, by examining multiple discrete tissue sites in the lungs of six subjects removed at the time of transplantation. We performed BAL on three never-smokers (NS) with normal spirometry, seven smokers with normal spirometry ("healthy smokers", HS), and four subjects with COPD (CS). Bacterial 16 s sequences were found in all subjects, without significant quantitative differences between groups. Both taxonomy-based and taxonomy-independent approaches disclosed heterogeneity in the bacterial communities between HS subjects that was similar to that seen in healthy NS and two mild COPD patients. The moderate and severe COPD patients had very limited community diversity, which was also noted in 28% of the healthy subjects. Both approaches revealed extensive membership overlap between the bacterial communities of the three study groups. No genera were common within a group but unique across groups. Our data suggests the existence of a core pulmonary bacterial microbiome that includes Pseudomonas, Streptococcus, Prevotella, Fusobacterium, Haemophilus, Veillonella, and Porphyromonas. Most strikingly, there were significant micro-anatomic differences in bacterial communities within the same lung of subjects with advanced COPD. These studies are further demonstration of the pulmonary microbiome and highlight global and micro-anatomic changes in these bacterial communities in severe COPD patients.
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