Robustness Through Regime Flips in Collapsing Ecological Networks

© 2019, Crown. There has been considerable progress in our perception of organized complexity in recent years. Recurrent debates on the dynamics and stability of complex systems have provided several insights, but it is very difficult to find identifiable patterns in the relationship between complex network structure and dynamics. Traditionally an arena for theoreticians, much of this research has been invigorated by demonstration of alternate stable states in real world ecosystems such as lakes, coral reefs, forests and grasslands. In this work, we use topological connectivity attributes of eighty six ecological networks and link these with random and targeted perturbations, to obtain general patterns of behaviour of complex real world systems. We have analyzed the response of each ecological network to individual, grouped and cascading extinctions, and the results suggest that most networks are robust to loss of specialists until specific thresholds are reached in terms of network geodesics. If the extinctions persist beyond these thresholds, a state change or ‘flip’ occurs and the structural properties are altered drastically, although the network does not collapse. As opposed to simpler or smaller networks, we find larger networks to contain multiple states that may in turn, ensure long-term persistence, suggesting that complexity can endow resilience to ecosystems. The concept of critical transitions in ecological networks and the implications of these findings for complex systems characterized by networks are likely to be profound with immediate significance for ecosystem conservation, invasion biology and restoration ecology.Non

Spatial Guilds in the Serengeti Food Web Revealed by a Bayesian Group Model

Food webs, networks of feeding relationships among organisms, provide fundamental insights into mechanisms that determine ecosystem stability and persistence. Despite long-standing interest in the compartmental structure of food webs, past network analyses of food webs have been constrained by a standard definition of compartments, or modules, that requires many links within compartments and few links between them. Empirical analyses have been further limited by low-resolution data for primary producers. In this paper, we present a Bayesian computational method for identifying group structure in food webs using a flexible definition of a group that can describe both functional roles and standard compartments. The Serengeti ecosystem provides an opportunity to examine structure in a newly compiled food web that includes species-level resolution among plants, allowing us to address whether groups in the food web correspond to tightly-connected compartments or functional groups, and whether network structure reflects spatial or trophic organization, or a combination of the two. We have compiled the major mammalian and plant components of the Serengeti food web from published literature, and we infer its group structure using our method. We find that network structure corresponds to spatially distinct plant groups coupled at higher trophic levels by groups of herbivores, which are in turn coupled by carnivore groups. Thus the group structure of the Serengeti web represents a mixture of trophic guild structure and spatial patterns, in contrast to the standard compartments typically identified in ecological networks. From data consisting only of nodes and links, the group structure that emerges supports recent ideas on spatial coupling and energy channels in ecosystems that have been proposed as important for persistence.Comment: 28 pages, 6 figures (+ 3 supporting), 2 tables (+ 4 supporting

Biology, Methodology or Chance? The Degree Distributions of Bipartite Ecological Networks

The distribution of the number of links per species, or degree distribution, is widely used as a summary of the topology of complex networks. Degree distributions have been studied in a range of ecological networks, including both mutualistic bipartite networks of plants and pollinators or seed dispersers and antagonistic bipartite networks of plants and their consumers. The shape of a degree distribution, for example whether it follows an exponential or power-law form, is typically taken to be indicative of the processes structuring the network. The skewed degree distributions of bipartite mutualistic and antagonistic networks are usually assumed to show that ecological or co-evolutionary processes constrain the relative numbers of specialists and generalists in the network. I show that a simple null model based on the principle of maximum entropy cannot be rejected as a model for the degree distributions in most of the 115 bipartite ecological networks tested here. The model requires knowledge of the number of nodes and links in the network, but needs no other ecological information. The model cannot be rejected for 159 (69%) of the 230 degree distributions of the 115 networks tested. It performed equally well on the plant and animal degree distributions, and cannot be rejected for 81 (70%) of the 115 plant distributions and 78 (68%) of the animal distributions. There are consistent differences between the degree distributions of mutualistic and antagonistic networks, suggesting that different processes are constraining these two classes of networks. Fit to the MaxEnt null model is consistently poor among the largest mutualistic networks. Potential ecological and methodological explanations for deviations from the model suggest that spatial and temporal heterogeneity are important drivers of the structure of these large networks

Conceptual Frameworks and Methods for Advancing Invasion Ecology

Invasion ecology has much advanced since its early beginnings. Nevertheless, explanation, prediction, and management of biological invasions remain difficult. We argue that progress in invasion research can be accelerated by, first, pointing out difficulties this field is currently facing and, second, looking for measures to overcome them. We see basic and applied research in invasion ecology confronted with difficulties arising from (A) societal issues, e.g., disparate perceptions of invasive species; (B) the peculiarity of the invasion process, e.g., its complexity and context dependency; and (C) the scientific methodology, e.g., imprecise hypotheses. To overcome these difficulties, we propose three key measures: (1) a checklist for definitions to encourage explicit definitions; (2) implementation of a hierarchy of hypotheses (HoH), where general hypotheses branch into specific and precisely testable hypotheses; and (3) platforms for improved communication. These measures may significantly increase conceptual clarity and enhance communication, thus advancing invasion ecology

Understanding the benefit of metformin use in cancer treatment

Biguanides have been developed for the treatment of hyperglycemia and type 2 diabetes. Recently, metformin, the most widely prescribed biguanide, has emerged as a potential anticancer agent. Epidemiological, preclinical and clinical evidence supports the use of metformin as a cancer therapeutic. The ability of metformin to lower circulating insulin may be particularly important for the treatment of cancers known to be associated with hyperinsulinemia, such as those of the breast and colon. Moreover, metformin may exhibit direct inhibitory effects on cancer cells by inhibiting mammalian target of rapamycin (mTOR) signaling and protein synthesis. The evidence supporting a role for metformin in cancer therapy and its potential molecular mechanisms of action are discussed

Association Patterns in Saproxylic Insect Networks in Three Iberian Mediterranean Woodlands and Their Resistance to Microhabitat Loss

The assessment of the relationship between species diversity, species interactions and environmental characteristics is indispensable for understanding network architecture and ecological distribution in complex networks. Saproxylic insect communities inhabiting tree hollow microhabitats within Mediterranean woodlands are highly dependent on woodland configuration and on microhabitat supply they harbor, so can be studied under the network analysis perspective. We assessed the differences in interacting patterns according to woodland site, and analysed the importance of functional species in modelling network architecture. We then evaluated their implications for saproxylic assemblages’ persistence, through simulations of three possible scenarios of loss of tree hollow microhabitat. Tree hollow-saproxylic insect networks per woodland site presented a significant nested pattern. Those woodlands with higher complexity of tree individuals and tree hollow microhabitats also housed higher species/interactions diversity and complexity of saproxylic networks, and exhibited a higher degree of nestedness, suggesting that a higher woodland complexity positively influences saproxylic diversity and interaction complexity, thus determining higher degree of nestedness. Moreover, the number of insects acting as key interconnectors (nodes falling into the core region, using core/periphery tests) was similar among woodland sites, but the species identity varied on each. Such differences in insect core composition among woodland sites suggest the functional role they depict at woodland scale. Tree hollows acting as core corresponded with large tree hollows near the ground and simultaneously housing various breeding microsites, whereas core insects were species mediating relevant ecological interactions within saproxylic communities, e.g. predation, competitive or facilitation interactions. Differences in network patterns and tree hollow characteristics among woodland sites clearly defined different sensitivity to microhabitat loss, and higher saproxylic diversity and woodland complexity showed positive relation with robustness. These results highlight that woodland complexity goes hand in hand with biotic and ecological complexity of saproxylic networks, and together exhibited positive effects on network robustness.The research Projects I+D CGL2011-23658 y CGL2012-31669 of the Spanish Minister of Science provided economic support

Metformin as an Adjunctive Therapy for Pancreatic Cancer: A Review of the Literature on Its Potential Therapeutic Use

Pancreatic ductal adenocarcinoma has the worst prognosis of any cancer. New adjuvant chemotherapies are urgently required, which are well tolerated by patients with unresectable cancers. This paper reviews the existing proof of concept data, namely laboratory, pharmacoepidemiological, experimental medicine and clinical trial evidence for investigating metformin in patients with pancreatic ductal adenocarcinoma. Laboratory evidence shows metformin inhibits mitochondrial ATP synthesis which directly and indirectly inhibits carcinogenesis. Drug–drug interactions of metformin with proton pump inhibitors and histamine H2-receptor antagonists may be of clinical relevance and pertinent to future research of metformin in pancreatic ductal adenocarcinoma. To date, most cohort studies have demonstrated a positive association with metformin on survival in pancreatic ductal adenocarcinoma, although there are many methodological limitations with such study designs. From experimental medicine studies, there are sparse data in humans. The current trials of metformin have methodological limitations. Two small randomized controlled trials (RCTs) reported null findings, but there were potential inequalities in cancer staging between groups and poor compliance with the intervention. Proof of concept data, predominantly from laboratory work, supports assessing metformin as an adjunct for pancreatic ductal adenocarcinoma in RCTs. Ideally, more experimental medicine studies are needed for proof of concept. However, many feasibility criteria need to be answered before such trials can progress

A depauperate immune repertoire precedes evolution of sociality in bees

Background Sociality has many rewards, but can also be dangerous, as high population density and low genetic diversity, common in social insects, is ideal for parasite transmission. Despite this risk, honeybees and other sequenced social insects have far fewer canonical immune genes relative to solitary insects. Social protection from infection, including behavioral responses, may explain this depauperate immune repertoire. Here, based on full genome sequences, we describe the immune repertoire of two ecologically and commercially important bumblebee species that diverged approximately 18 million years ago, the North American Bombus impatiens and European Bombus terrestris. Results We find that the immune systems of these bumblebees, two species of honeybee, and a solitary leafcutting bee, are strikingly similar. Transcriptional assays confirm the expression of many of these genes in an immunological context and more strongly in young queens than males, affirming Bateman’s principle of greater investment in female immunity. We find evidence of positive selection in genes encoding antiviral responses, components of the Toll and JAK/STAT pathways, and serine protease inhibitors in both social and solitary bees. Finally, we detect many genes across pathways that differ in selection between bumblebees and honeybees, or between the social and solitary clades. Conclusions The similarity in immune complement across a gradient of sociality suggests that a reduced immune repertoire predates the evolution of sociality in bees. The differences in selection on immune genes likely reflect divergent pressures exerted by parasites across social contexts

Signaling Networks Associated with AKT Activation in Non-Small Cell Lung Cancer (NSCLC): New Insights on the Role of Phosphatydil-Inositol-3 kinase

Aberrant activation of PI3K/AKT signalling represents one of the most common molecular alterations in lung cancer, though the relative contribution of the single components of the cascade to the NSCLC development is still poorly defined. In this manuscript we have investigated the relationship between expression and genetic alterations of the components of the PI3K/AKT pathway [KRAS, the catalytic subunit of PI3K (p110α), PTEN, AKT1 and AKT2] and the activation of AKT in 107 surgically resected NSCLCs and have analyzed the existing relationships with clinico-pathologic features. Expression analysis was performed by immunohistochemistry on Tissue Micro Arrays (TMA); mutation analysis was performed by DNA sequencing; copy number variation was determined by FISH. We report that activation of PI3K/AKT pathway in Italian NSCLC patients is associated with high grade (G3–G4 compared with G1–G2; n = 83; p<0.05) and more advanced disease (TNM stage III vs. stages I and II; n = 26; p<0.05). In addition, we found that PTEN loss (41/104, 39%) and the overexpression of p110α (27/92, 29%) represent the most frequent aberration observed in NSCLCs. Less frequent molecular lesions comprised the overexpression of AKT2 (18/83, 22%) or AKT1 (17/96, 18%), and KRAS mutation (7/63, 11%). Our results indicate that, among all genes, only p110α overexpression was significantly associated to AKT activation in NSCLCs (p = 0.02). Manipulation of p110α expression in lung cancer cells carrying an active PI3K allele (NCI-H460) efficiently reduced proliferation of NSCLC cells in vitro and tumour growth in vivo. Finally, RNA profiling of lung epithelial cells (BEAS-2B) expressing a mutant allele of PIK3 (E545K) identified a network of transcription factors such as MYC, FOS and HMGA1, not previously recognised to be associated with aberrant PI3K signalling in lung cancer

Targeting cancer metabolism: a therapeutic window opens

Genetic events in cancer activate signalling pathways that alter cell metabolism. Clinical evidence has linked cell metabolism with cancer outcomes. Together, these observations have raised interest in targeting metabolic enzymes for cancer therapy, but they have also raised concerns that these therapies would have unacceptable effects on normal cells. However, some of the first cancer therapies that were developed target the specific metabolic needs of cancer cells and remain effective agents in the clinic today. Research into how changes in cell metabolism promote tumour growth has accelerated in recent years. This has refocused efforts to target metabolic dependencies of cancer cells as a selective anticancer strategy.Burroughs Wellcome FundSmith Family FoundationStarr Cancer ConsortiumDamon Runyon Cancer Research FoundationNational Institutes of Health (U.S.