Real-world Ecosystem Research Articles

Sodium-glucose cotransporter 2 inhibitors reduce the risk of incident type 2 diabetes in people with heart failure without diabetes: An analysis of real-world, cohort data.

Sodium-glucose cotransporter 2 inhibitors (SGLT2is), used as a glucose-lowering therapy in people with type 2 diabetes (T2D), have significant cardiorenal benefits, reducing hospitalization for heart failure (HF) and cardiovascular mortality in patients with and without T2D. Recent clinical trial evidence suggests their potential utility in preventing incident T2D among the high-risk HF populations. Therefore, we aimed to assess whether this finding was reproducible in a real-world setting. We performed a retrospective cohort analysis of 484 643 patients with HF, without baseline diabetes, prescribed either angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers with/without SGLT2is (treatment, n = 42 018; reference, n = 442 625) across 95 global health care organizations, using a large real-world ecosystem. Propensity score matching balanced arms 1:1 for confounders (n = 39 168 each arm). Subgroup analysis further evaluated the impact on patients with prediabetes and the efficacy of dapagliflozin/empagliflozin, specifically, on incident T2D and secondary outcomes, including all-cause mortality, acute pulmonary oedema and hospitalization. Treatment with SGLT2is significantly reduced incident T2D {hazard ratio (HR) 0.71 [95% confidence interval (CI) 0.63, 0.75]} in patients with HF. The analysis of patients with prediabetes found that SGLT2is further reduced incident T2D [HR 0.62 (95% CI 0.45, 0.80)]. The magnitude of reduction in incident T2D was higher in patients prescribed dapagliflozin [HR 0.47 (95% CI 0.39, 0.56)] versus empagliflozin [HR 0.81 (95% CI 0.70, 0.93)]. Treatment with SGLT2is in patients with HF was associated with a reduced risk of incident T2D, most strikingly in people with prediabetes.

The Representational Challenge for Designing and Managing 5P Medicine Ecosystems.

Health and social care systems around the globe currently undergo a transformation towards personalized, preventive, predictive, participative precision medicine (5PM), considering the individual health status, conditions, genetic and genomic dispositions, etc., in personal, social, occupational, environmental and behavioral context. This transformation is strongly supported by technologies such as micro- and nanotechnologies, advanced computing, artificial intelligence, edge computing, etc. For enabling communication and cooperation between actors from different domains using different methodologies, languages and ontologies based on different education, experiences, etc., we have to understand the transformed health ecosystems and all its components in structure, function and relationships in the necessary detail ranging from elementary particles up to the universe. That way, we advance design and management of the complex and highly dynamic ecosystem from data to knowledge level. The challenge is the consistent, correct and formalized representation of the transformed health ecosystem from the perspectives of all domains involved, representing and managing them based on related ontologies. The resulting business view of the real-world ecosystem must be interrelated using the ISO/IEC 21838 Top Level Ontologies standard. Thereafter, the outcome can be transformed into implementable solutions using the ISO/IEC 10746 Open Distributed Processing Reference Model. Model and framework for this system-oriented, architecture-centric, ontology-based, policy-driven approach have been developed by the first author and meanwhile standardized as ISO 23903 Interoperability and Integration Reference Architecture.

Cardiovascular Outcomes with Intravitreal Anti-Vascular Endothelial Growth Factor Therapy in Patients with Diabetes: A Real-World Data Analysis.

Anti-vascular endothelial growth factor (anti-VEGF) therapy is commonly used intravitreally for diabetic proliferative retinopathy, but when used systemically for treating cancers, an excess of cardiovascular disease (CVD) events has been noted. The latter is of concern for people with diabetes, who are at higher risk of CVD. This study aims to explore the relationship between incident CVD and intravitreal anti-VEGF therapy in patients with diabetes, compared to other therapies, using a large real-world global federated dataset. Data were analysed using TriNetX, a global electronic medical real-world ecosystem. The study included adults with diabetes and excluded those with a history of CVD prior to the time window of data extraction. Patients were categorised into two cohorts: anti-VEGF therapy or control cohort (laser or steroid therapies). The cohorts were 1:1 propensity score-matched for age, sex, ethnicity, body mass index, systolic blood pressure, HbA1c, and cardiovascular medications. Outcomes analysed at 1, 6 and 12months were: (1) mortality; (2) acute myocardial infarction (MI); (3) cerebral infarction; and (4) heart failure. Relative risk analyses were performed using the built-in R statistical computing platform on TriNetX. In patients with diabetes (n = 2205; mean age 58.8 ± 15.8, Stddiff 0.05; 56% male), anti-VEGF therapy was associated with a numerical but non-statistically significant increased CVD risk over 1, 6, and 12months: Mortality over 1month (RR 1; 95%CI 0.42, 2.40), 6months (RR 1.46; 95%CI 0.72, 2.95) and 12months (RR 1.41; 95%CI 0.88, 2.27). There was no excess of acute MI over 1 (RR n/a: not applicable; 0/0: 0 events in the anti-VEGF group/0 events in the control group), 6 and 12months (RR n/a; 0/10 events); cerebral infarction over 1, 6months (RR n/a; 0/0 events), and 12months (RR n/a; 0/10); and heart failure over 1month (RR n/a; 0/0 events), 6months (RR 1; 95%CI 0.42, 2.40) and 12months (RR 1; 95%CI 0.42, 2.34). There was no statistically significant risk of cardiovascular-related events in the short or medium term in patients with diabetes who received intravitreal anti-VEGF therapy, despite a small increase in the number of CVD events. Our study supports the real-world safety of intravitreal anti-VEGF therapy in patients with diabetes free of baseline CVD.

Bioinspired “cage traps” for closed-loop lead management of perovskite solar cells under real-world contamination assessment

Despite the remarkable progress made in perovskite solar cells, great concerns regarding potential Pb contamination risk and environmental vulnerability risks associated with perovskite solar cells pose a significant obstacle to their real-world commercialization. In this study, we took inspiration from the ensnaring prey behavior of spiders and chemical components in spider web to strategically implant a multifunctional mesoporous amino-grafted-carbon net into perovskite solar cells, creating a biomimetic cage traps that could effectively mitigate Pb leakage and shield the external invasion under extreme weather conditions. The synergistic Pb capturing mechanism in terms of chemical chelation and physical adsorption is in-depth explored. Additionally, the Pb contamination assessment of end-of-life perovskite solar cells in the real-world ecosystem, including Yellow River water and soil, is proposed. The sustainable closed-loop Pb management process is also successfully established involving four critical steps: Pb precipitation, Pb adsorption, Pb desorption, and Pb recycling. Our findings provide inspiring insights for promoting green and sustainable industrialization of perovskite solar cells.

Calcium carbonate alters the functional response of coastal sediments to eutrophication-induced acidification

Coastal ocean acidification research is dominated by laboratory-based studies that cannot necessarily predict real-world ecosystem response given its complexity. We enriched coastal sediments with increasing quantities of organic matter in the field to identify the effects of eutrophication-induced acidification on benthic structure and function, and assess whether biogenic calcium carbonate (CaCO3) would alter the response. Along the eutrophication gradient we observed declines in macrofauna biodiversity and impaired benthic net primary productivity and sediment nutrient cycling. CaCO3 addition did not alter the macrofauna community response, but significantly dampened negative effects on function (e.g. net autotrophy occurred at higher levels of organic matter enrichment in +CaCO3 treatments than −CaCO3 (1400 vs 950 g dw m−2)). By identifying the links between eutrophication, sediment biogeochemistry and benthic ecosystem structure and function in situ, our study represents a crucial step forward in understanding the ecological effects of coastal acidification and the role of biogenic CaCO3 in moderating responses.

Existence of spatial patterns in reaction–diffusion systems incorporating a prey refuge

Abstract. In real-world ecosystem, studies on the mechanisms of spatiotemporal pattern formation in a system of interacting populations deserve special attention for its own importance in contemporary theoretical ecology. The present investigation deals with the spatial dynamical system of a two-dimensional continuous diffusive predator–prey model involving the influence of intra-species competition among predators with the incorporation of a constant proportion of prey refuge. The linear stability analysis has been carried out and the appropriate condition of Turing instability around the unique positive interior equilibrium point of the present model system has been determined. Furthermore, the existence of the various spatial patterns through diffusion-driven instability and the Turing space in the spatial domain have been explored thoroughly. The results of numerical simulations reveal the dynamics of population density variation in the formation of isolated groups, following spotted or stripe-like patterns or coexistence of both the patterns. The results of the present investigation also point out that the prey refuge does have significant influence on the pattern formation of the interacting populations of the model under consideration.

The up-scaling of ecosystem functions in a heterogeneous world

Earth is in the midst of a biodiversity crisis that is impacting the functioning of ecosystems and the delivery of valued goods and services. However, the implications of large scale species losses are often inferred from small scale ecosystem functioning experiments with little knowledge of how the dominant drivers of functioning shift across scales. Here, by integrating observational and manipulative experimental field data, we reveal scale-dependent influences on primary productivity in shallow marine habitats, thus demonstrating the scalability of complex ecological relationships contributing to coastal marine ecosystem functioning. Positive effects of key consumers (burrowing urchins, Echinocardium cordatum) on seafloor net primary productivity (NPP) elucidated by short-term, single-site experiments persisted across multiple sites and years. Additional experimentation illustrated how these effects amplified over time, resulting in greater primary producer biomass sediment chlorophyll a content (Chla) in the longer term, depending on climatic context and habitat factors affecting the strengths of mutually reinforcing feedbacks. The remarkable coherence of results from small and large scales is evidence of real-world ecosystem function scalability and ecological self-organisation. This discovery provides greater insights into the range of responses to broad-scale anthropogenic stressors in naturally heterogeneous environmental settings.

Abundance of common species, not species richness, drives delivery of a real-world ecosystem service.

Biodiversity-ecosystem functioning experiments have established that species richness and composition are both important determinants of ecosystem function in an experimental context. Determining whether this result holds for real-world ecosystem services has remained elusive, however, largely due to the lack of analytical methods appropriate for large-scale, associational data. Here, we use a novel analytical approach, the Price equation, to partition the contribution to ecosystem services made by species richness, composition and abundance in four large-scale data sets on crop pollination by native bees. We found that abundance fluctuations of dominant species drove ecosystem service delivery, whereas richness changes were relatively unimportant because they primarily involved rare species that contributed little to function. Thus, the mechanism behind our results was the skewed species-abundance distribution. Our finding that a few common species, not species richness, drive ecosystem service delivery could have broad generality given the ubiquity of skewed species-abundance distributions in nature.

Experimenting with ecosystem interaction networks in search of threshold potentials in real-world marine ecosystems.

Thresholds profoundly affect our understanding and management of ecosystem dynamics, but we have yet to develop practical techniques to assess the risk that thresholds will be crossed. Combining ecological knowledge of critical system interdependencies with a large-scale experiment, we tested for breaks in the ecosystem interaction network to identify threshold potential in real-world ecosystem dynamics. Our experiment with the bivalves Macomona liliana and Austrovenus stutchburyi on marine sandflats in New Zealand demonstrated that reductions in incident sunlight changed the interaction network between sediment biogeochemical fluxes, productivity, and macrofauna. By demonstrating loss of positive feedbacks and changes in the architecture of the network, we provide mechanistic evidence that stressors lead to break points in dynamics, which theory predicts predispose a system to a critical transition.

Behavioural Adaptation Towards Efficient Resource Sharing under the Lack of Communication

This paper introduces a novel multi-agent model for simulating water sharing scenarios under various irrigation policies, together with a novel self adaptive learning algorithm that achieves efficient resource allocation. The main contribution of this work lies in the fact that both the multi-agent model and the proposed learning algorithm operate under the lack of communication between the users of the resource, thus, no assumptions about the development of relations of trust between them are made. Moreover, the proposed learning algorithm uses only local information and operates in a decentralized manner, thus its implementation does not entail significant costs. The model was calibrated using data from a real world ecosystem and experimental results provided statistical and qualitative figures of merit for assessing typical irrigation policies. For all the irrigation policies examined, even if the users of the resource acted under profit maximization criteria, the proposed learning algorithm provided a means of achieving efficient resource allocation, despite the lack of communication. Thus, the proposed model and learning algorithm are valuable tools for assessing alternative irrigation policies and providing the best policy for any given scenario.