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The separation of macro-level and microbial food webs is typical but has important limits. A multilayered food web conceptual model is needed because microbial food webs are nested within macro-organisms. These multilayered microbial food webs likely influence the network dynamics of macro-level food webs. A multilayered food webs model opens new avenues for empirical investigations into the complexity of ecological networks. The model can provide a new lens through which to view a network's response to ecosystem changes. Food webs are typically defined as being macro-organism-based (e.g., plants, mammals, birds) or microbial (e.g., bacteria, fungi, viruses). However, these characterizations have limits. We propose a multilayered food web conceptual model where microbial food webs are nested within food webs composed of macro-organisms. Nesting occurs through host–microbe interactions, which influence the health and behavior of host macro-organisms, such that host microbiomes likely alter population dynamics of interacting macro-organisms and vice versa. Here, we explore the theoretical underpinnings of multilayered food webs and the implications of this new conceptual model on food web ecology. Our framework opens avenues for new empirical investigations into complex ecological networks and provides a new lens through which to view a network's response to ecosystem changes. [ABSTRACT FROM AUTHOR]

• The study investigates changes in species richness, interaction diversity, and the interactive role of apis mellifera within plant-bee interaction networks along an elevational gradient. • Results show a decrease in the richness of plants, bees, and interaction diversity with increasing elevation, indicating potential climatic filtering effects. • Despite being a super generalist species, the interactive role of A. mellifera within networks also decreases with elevation, suggesting its response to environmental gradients. The honeybee Apis mellifera is an introduced managed pollinator species in many world regions and exhibits a high capacity to compete for resources against native bee species. Despite empirical evidence showing that A. mellifera establishes a great number of interactions within plant-bee interaction networks (i.e., high interactive role), little is known on whether its interactive role changes along elevational gradients. Being motivated by these concerns, here we assessed the species richness of plants, bees, interaction diversity, and the interactive role of A. mellifera within plant-bee interaction networks along an elevation gradient from the coastal dunes (4 m.a.s.l.) of the Gulf of Mexico up to the pine-fir forests (3425 m.a.s.l.) in the extinct volcano Cofre de Perote in Mexico. Moreover, we evaluated the interactive role of A. mellifera 's on the diversity of plant-bee interactions along this elevational gradient. We found a decrease in the richness of plants, bees, interaction diversity as elevation increased, and the interactive role of A. mellifera within the networks also decreased with elevation. Moreover, the interactive role of A. mellifera had no effect on the diversity of plant-bee interactions along the studied elevational gradient. These findings indicate that climatic conditions could be filtering plant and bee species and their interactions, even the interactions of a super generalist species as A. mellifera. In short, our study helps understand the responses of species and their biotic interactions over Neotropical elevational gradients. By examining the pronounced climatic shifts, similar to those induced by climate change, we also highlight the sensitivity of these responses to significant environmental alterations. Our findings underscore the critical importance of understanding ecological dynamics in the face of rapidly changing climates. [ABSTRACT FROM AUTHOR]

Interaction prediction is a crucial task in the Social Internet of Things (SIoT), serving diverse applications including social network analysis and recommendation systems. However, the dynamic nature of items, users, and their interactions over time poses challenges in effectively capturing and analyzing these changes. Existing interaction prediction models often overlook the temporal aspect and lack the ability to model multi-relational user-item interactions over time. To address these limitations, in this paper, we propose a S tructure, F acticity, and T emporal information preservation e mbedding model (SFTe) to predict future interaction. Our model leverages the advantages of Temporal Knowledge Graphs (TKGs) that can capture both the multi-relations and evolution. We begin by modeling user-item interactions over time by constructing a Temporal Interaction Knowledge Graph (TIKG). We then employ Structure Embedding (SE), Facticity Embedding (FE), and Temporal Embedding (TE) to capture topological structure, facticity consistency, and temporal dependence, respectively. In SE, we focus on preserving the first-order relationships to capture the topological structure of TIKG. In the FE component, given the distinct nature of SIoT, we introduce an attention mechanism to capture the effect of entities with the same additional information for generating subgraph embeddings. Lastly, TE utilizes recurrent neural networks to model the temporal dependencies among subgraphs and capture the evolving dynamics of the interactions over time. Experimental results on standard future interaction prediction demonstrate the superiority of the SFTe model compared with the state-of-the-art methods. Our model effectively addresses the challenges of time-aware interaction prediction, showcasing the potential of TKGs to enhance prediction performance. [ABSTRACT FROM AUTHOR]

Human activities, particularly urbanization, profoundly impact ecosystems often resulting in biotic homogenization. Whether or not urban landscapes can sustain diverse pollinator and plant communities is an important question to be addressed. Here, we investigated the influence of urbanization on plant-hummingbird interaction networks in a large tropical city, Belo Horizonte, Brazil. We recorded 13198 legitimate interactions between seven hummingbirds and 57 plant species across 12 local networks. Urban landscapes exhibited predominantly generalized networks, maintaining this pattern across varying vegetation cover and floral resource abundance. Although some functionally specialized hummingbirds with long bills were recorded performing more specialized interactions, urban environments did not generally support specialized networks. Nevertheless, network specialization did increase with the proportion of native nectar plants, emphasizing their importance for maintaining some specialized interactions. Furthermore, we observed a positive effect of plant richness, but not of flower abundance, on hummingbird abundance, indicating that it is not only the amount of flowers, but the diversity of floral resources that may be a key factor in maintaining hummingbirds. Therefore, promoting a diverse assemblage of native plants in urban green areas is crucial for sustainable pollinator communities. Our study highlights that while a biodiverse urban landscape will require careful urban vegetation planning considering both floral resource diversity and availability, vegetation cover per se may not be sufficient to mitigate the negative impacts of urbanization. Maintaining a diverse vegetation with different life forms, flowering phenology, and especially of native plants across the urban landscape is needed to create welcoming spaces for pollinators. [Display omitted] • Hummingbirds are important pollinators found in urban areas across the Americas. • Generalized interaction networks predominated across the urban landscape. • Specific types of vegetation should be considered in urban green spaces. • Importance of native flora to support specialized interactions for hummingbirds. [ABSTRACT FROM AUTHOR]

Empirical evidence has shown that introduced honeybees, Apis mellifera L., can change the structural organization of ecological networks involving pollinators and flowering plants. In this case, studies have shown that A. mellifera is highly connected within networks (i.e., high interactive role) mainly due to its high abundances, long colony lifetime, generalist diet, and great capacity of spread and adaptation to new environments. However, there is little knowledge on how the interactive role of A. mellifera in these flower-visitor networks changes spatially and the potential correlates of such variation across ecological and geographical gradients worldwide. In this study, we evaluated how native and exotic distribution ranges, local climate, human influence (i.e., anthropogenic disturbance), and latitude shape the interactive role of the honeybee in plant-floral visitor networks globally. To achieve that, we compiled 95 weighted plant-floral visitor networks encompassing ca. 87 degrees of latitude and 227 degrees of longitude across the globe. We found that the interactive role of A. mellifera is higher in its exotic range than in the native distributional range and positively associated with mean annual temperature and precipitation. Further, the interactive role of A. mellifera was high at intermediate values of global human influence and increased with latitude. Our findings help us to understand how different drivers related to rapid global change could affect the capacity of A. mellifera to colonize and increase its impact on other pollinator species in different environments. [ABSTRACT FROM AUTHOR]

• Borrelia, Rickettsia and Babesia were detected in the Orinoquia region, Colombia. • A total of 734 mammals (655 wild and 79 domestics) were analyzed. • Pathogen detection on 272 ticks collected while feeding from 96 mammals. • Pathogen detection in 93 mammals (blood, heart, liver, lung and kidney). • Interaction networks: 18 mammal and seven tick species, interacting with pathogens. The hard tick clade (Ixodidae) currently comprises 762 species worldwide (266 Prostriata and 496 Metastriata). A quarter of hard ticks are found in the Neotropical region, and 42 species have been documented in Colombia. Ixodidae species are important vectors of pathogens such as bacteria, helminths, protozoa, and viruses. In tick-borne diseases, vertebrate hosts perform an important role in the transmission, maintenance, and spread of pathogens. Colombia ranks sixth among countries with the highest mammal biodiversity, with a total of 548 species, where some of these species may be involved in pathogen transmission cycles with ticks as vectors. This research evaluated the presence of two genera of bacteria (Borrelia and Rickettsia) and the protozoan (Babesia) in ticks and mammals in the Orinoquia region of Colombia, establishing interaction networks. The information comes from 734 mammals (655 wild and 79 domestic), belonging to 59 species. Tick infestation (n = 1,805) was found with 14.85 % (n = 109) of the examined mammals and corresponds to nine tick species confirmed morphologically and molecularly. To detect pathogens 272 ticks were collected while feeding on 96 mammals; samples from 93 mammals were analyzed. The presence of borreliae from the relapsing fever group (RFG) and the Lyme disease group (LDG) were detected. Rickettsia spp. was detected in ticks and mammals, while Babesia bigemina was only detected in ticks. This research is the first to address the prevalence of zoonotic pathogens in domestic and wild mammals infested with hard ticks in the Department of Arauca, Colombia. Considering that reporting cases of infections with Babesia, Borrelia , and Rickettsia in Colombia is not mandatory, their impact on public health cannot be estimated. This highlights the importance of continuously detecting, confirming, and identifying these and other important pathogens within the "One Health" framework, as they have a significant economic and medical-veterinary impact globally. [Display omitted] [ABSTRACT FROM AUTHOR]

Researchers worldwide with great endeavor searching and repurpose drugs might be potentially useful in fighting newly emerged coronavirus. These drugs show inhibition but also show side effects and complications too. On December 27, 2020, 80,926,235 cases have been reported worldwide. Specifically, in Pakistan, 471,335 has been reported with inconsiderable deaths. Identification of COVID-19 drugs pathway through drug-gene and gene−gene interaction to find out the most important genes involved in the pathway to deal with the actual cause of side effects beyond the beneficent effects of the drugs. The medicines used to treat COVID-19 are retrieved from the Drug Bank. The drug-gene interaction was performed using the Drug Gene Interaction Database to check the relation between the genes and the drugs. The networks of genes are developed by Gene MANIA, while Cytoscape is used to check the active functional association of the targeted gene. The developed systems cross-validated using the EnrichNet tool and identify drug genes' concerned pathways using Reactome and STRING. Five drugs Azithromycin, Bevacizumab, CQ, HCQ, and Lopinavir, are retrieved. The drug-gene interaction shows several genes that are targeted by the drug. Gene MANIA interaction network shows the functional association of the genes like co-expression, physical interaction, predicted, genetic interaction, co-localization, and shared protein domains. Our study suggests the pathways for each drug in which targeted genes and medicines play a crucial role, which will help experts in-vitr o overcome and deal with the side effects of these drugs, as we find out the in-silico gene analysis for the COVID-19 drugs. [ABSTRACT FROM AUTHOR]

Microbiology has unraveled rich evidence of ongoing reticulate evolutionary processes and complex interactions both within and between cells. These phenomena feature real biological networks, which can logically be analyzed using network-based tools. It is thus not surprising that network sciences, a field independent from evolutionary biology and microbiology, have recently pervasively infused their methods into both fields. Importantly, network tools bring forward observations enhancing the understanding of three core evolutionary concepts: variation, fitness, and heredity. Consequently, our work shows how network sciences can enhance evolutionary theory by explaining the evolution by natural selection of a broad diversity of units of selection, while updating the popular figure of Darwin's tree of life with a comprehensive sketch of the networks of evolution. Network sciences are introducing network-based models into all relevant biological fields, notably in microbiology and evolutionary biology. The three core principles of evolution – variation, heredity, and differential fitness – crystalized in the 1970s, still serve as a conceptual benchmark for the theory of evolution by natural selection. Network-based inquiries in microbiology tap into the complexity of the systems of interactions that underscore the evolutionary dynamics of cellular life, thereby augmenting our understanding of the three core principles of evolution. Conversely, the improved understanding of evolutionary dynamics provided by networks informs microbiology in various ways. The network-based understanding of evolution is often considered as anti-Darwinian in spirit, a claim that can be debunked using microbiology. [ABSTRACT FROM AUTHOR]

Listeria monocytogenes is a Gram positive foodborne pathogen that regularly causes outbreaks of systemic infectious diseases. The bacterium maintains a facultative intracellular lifestyle; it thrives under a variety of environmental conditions and is able to infect human host cells. L. monocytogenes is genetically tractable and therefore has become an attractive model system to study the mechanisms employed by facultative intracellular bacteria to invade eukaryotic cells and to replicate in their cytoplasm. Besides its importance for basic research, L. monocytogenes also serves as a paradigmatic pathogen in genomic epidemiology, where the relative stability of its genome facilitates successful outbreak detection and elucidation of transmission chains in genomic pathogen surveillance systems. In both terms, it is necessary to keep the annotation of the L. monocytogenes genome up to date. Therefore, we have created the database Listi Wiki (http://listiwiki.uni-goettingen.de/) which stores comprehensive information on the widely used L. monocytogenes reference strain EDG-e. Listi Wiki is designed to collect information on genes, proteins and RNAs and their relevant functional characteristics, but also further information such as mutant phenotypes, available biological material, and publications. In its present form, Listi Wiki combines the most recent annotation of the EDG-e genome with published data on gene essentiality, gene expression and subcellular protein localization. Listi Wiki also predicts protein-protein interactions networks based on protein homology to Bacillus subtilis proteins, for which detailed interaction maps have been compiled in the sibling database Subti Wiki. Furthermore, crystallographic information of proteins is made accessible through integration of Protein Structure Database codes and AlphaFold structure predictions. Listi Wiki is an easy-to-use web interface that has been developed with a focus on an intuitive access to all information. Use of Listi Wiki is free of charge and its content can be edited by all members of the scientific community after registration. In our labs, Listi Wiki has already become an important and easy to use tool to quickly access genome annotation details that we can keep updated with advancing knowledge. It also might be useful to promote the comprehensive understanding of the physiology and virulence of an important human pathogen. [ABSTRACT FROM AUTHOR]

Animal-plant interactions have a major influence on ecosystem structure and functioning. Understanding to what extent the temporal dynamics of interactions is determined by climate and disturbances is thus relevant to predict ecological and evolutionary outcomes in a changing world. Here, we assessed whether the temporal dynamics of ant-plant interactions in a mountainous fire-prone ecosystem is driven by seasonal variation in abiotic conditions, and to what extent fire disturbance alters this dynamic. We also examined the thermal responses of foliage-dwelling ants in order to predict the effects of seasonal oscillations of temperature on ant activity. To do so, we monitored ant-plant associations in 35 sampling plots for one year before an unmanaged fire has occurred. Then, 26 burned and nine unburned plots were monitored for another year after fire. We found that warmer and wetter conditions let to increases in the diversity and frequency of ant-plant interactions, mainly via upturns in plant resource availability and ant foraging activity. Beyond the positive effects of temperature on interaction networks, however, ant species exhibited a low heterogeneity and a huge overlap in thermal niches. Moreover, fire has led to short-term negative effects on the diversity and frequency of interactions in ant-plant networks. In spite of it, these network metrics in burned plots took up to half a year to return to similar levels from unburned plots, highlighting the resilience of ant-plant interactions after fire disturbances. This study shows that wide thermal niches of ant species and fire resilience likely beget ant-plant networks reliability over seasons. The high overlap and broad thermal niches of ant species interacting with plant resources suggest that ant diversity plays a minor role in the tolerance against climatic changes in this fire-adapted community. These findings open a new pathway to explore thermal responses of species and their ecological interactions in broader gradients of environmental conditions and ecosystem disturbances. We advocate that long-term studies comprising assisted burnings are desirable to forecast the impact of fire regimes and how their synergy with climate would affect the functioning of fire-prone ecosystems. Lastly, this study adds evidence that studied interaction networks can be useful to monitor the impacts of environmental changes such as anthropogenic disturbances, being representative of many even more complex species interactions in ecosystems. [ABSTRACT FROM AUTHOR]

Computational analysis of biomolecular interaction networks is now gaining a lot of importance to understand the functions of novel genes/proteins. Gene interaction (GI) network analysis and protein-protein interaction (PPI) network analysis play a major role in predicting the functionality of interacting genes or proteins and gives an insight into the functional relationships and evolutionary conservation of interactions among the genes. An interaction network is a graphical representation of gene/protein interactome, where each gene/protein is a node, and interaction between gene/protein is an edge. In this review, we discuss the popular open source databases that serve as data repositories to search and collect protein/gene interaction data, and also tools available for the generation of interaction network, visualization and network analysis. Also, various network analysis approaches like topological approach and clustering approach to study the network properties and functional enrichment server which illustrates the functions and pathway of the genes and proteins has been discussed. Hence the distinctive attribute mentioned in this review is not only to provide an overview of tools and web servers for gene and protein-protein interaction (PPI) network analysis but also to extract useful and meaningful information from the interaction networks. [ABSTRACT FROM AUTHOR]

• Time-lapse cameras were used to monitor species and individual-based networks. • Plants with lower centrality presented higher fitness in individual-based networks. • Plants with lower selectivity presented higher fitness in individual-based networks. • An individual-based network is a useful tool to understand plant fitness. In animal-pollinated plants, fitness is affected by pollinator attraction and plant-pollinator trait matching. Plant-pollinator interactions are often characterized using metrics derived from mutualistic networks, such as centrality and interaction selectivity. This approach often focuses on the species level, thus neglecting significant among-individual variation in attracting foraging pollinators and associated fitness consequences for plants. Here, we tested if centrality and interaction selectivity were related to fitness at the species and the individual level for 14 hummingbird-pollinated plant species in the Atlantic Forest. In addition, we tested if plant-pollinator trait-matching influenced plant fitness. At the species-level, we did not find a relationship between plant fitness and centrality nor interaction selectivity; we found instead that plant fitness increased with higher trait-matching between bill and corolla lengths. At the individual-level we found that individuals with higher centrality values produced less seeds, likely due to lower quality in pollen deposition. Moreover, individuals with a lower interaction selectivity also produced more seeds, probably because of higher conspecific pollen flow. Our results show that individual position and interaction selectivity within pollination networks may have important implications for pollination effectiveness and hence plant fitness. [ABSTRACT FROM AUTHOR]

Urbanization leads to the restructuring of plant-animal interactions due to environmental changes and introduction of non-native species that become part of local ecological processes. The conservation of pollinators in urban areas has received increasing attention. However, detailed quantification of available floral resources and their use by pollinators are rarely conducted. Here, we characterized the interaction network between hummingbirds and native and non-native plants, the behavior of resource use by pollinators and the temporal availability of nectar resources in an extensive urban green area from Brazil. We found that more than half of the interactions between hummingbirds and plants were illegitimate, which do not constitute potential pollination. The interaction network was generalized, indicating low level of niche partitioning, which is usual for urban environments. Inclusion of non-pollination interactions increased specialization. Although native and non-native plants provide a similar amount of nectar when considering each plant species for a given month, the latter contributed most to the total nectar availability owed to their higher abundance and longer flowering phenologies. Importantly, non-native plants provided resources when native flowers were scarce. Our results show how non-native plants may sometimes have relevant contributions for maintenance of pollinators in cities throughout the year, supporting them during periods of resource shortage. At the same time, urban pollinator-plant communities may be characterized by high prevalence of illegitimate interactions, which highlights the opportunistic use of resources by animals. In conclusion, our study suggests that biodiversity-friendly urban planning should consider the relevant role played by non-native species and that pollinator support may require different types of interactions with flowers. • We quantified temporal nectar availability and use by hummingbirds. • Non-native plants contributed substantially to nectar availability. • Native and non-native plants showed distinct phenologies. • Most visits were illegitimate, without touching the reproductive structures. • Pollinator conservation in urban areas should consider non-mutualistic interactions. [ABSTRACT FROM AUTHOR]

With the growing interest in social Peer-to-Peer (P2P) applications, relationships of individuals are further exploited to improve the performances of reputation systems. It is an on-going challenge to investigate how spatial reciprocity aids indirect reciprocity in sustaining cooperation in practical P2P environments. This paper describes the construction of an extended prisoner’s dilemma game on square lattice networks with three strategies, i.e., defection, unconditional cooperation, and reciprocal cooperation. Reciprocators discriminate partners according to their reputations based on image scoring, where mistakes in judgment of reputations may occur. The independent structures of interaction and learning neighborhood are discussed, with respect to the situation in which learning environments differ from interaction networks. The simulation results have indicated that the incentive mechanism enhances cooperation better in structured peers than among a well-mixed population. Given the realistic condition of inaccurate reputation scores, defection is still successfully held down when the players interact and learn within the unified neighborhoods. Extensive simulations have further confirmed the positive impact of spatial structure on cooperation with different sizes of lattice neighborhoods. And similar conclusions can also be drawn on regular random networks and scale-free networks. Moreover, for the separated structures of the neighborhoods, the interaction network has a critical effect on the evolution dynamics of cooperation and learning environments only have weaker impacts on the process. Our findings further provide some insights concerning the evolution of collective behaviors in social systems. [ABSTRACT FROM AUTHOR]

The interactions between birds that use tree cavities for breeding, roosting and sheltering have been named ‘nest webs’. We applied for the first time in nest-web studies some tools developed in network theory, in order to develop conservation and management recommendations of forest biodiversity. We recorded 109 interactions between 15 bird and 11 cavity-bearing tree species, in a subtropical piedmont forest (PF) of northwestern Argentina. Bird species in this nest-web included four woodpecker species, whose cavities were scarcely (9%) used by non-excavator birds, such as parrots, owls, and woodcreepers. Based on the Importance and Strength indices the most important tree species were Calycophyllum multiflorum (Rubiaceae) and Anadenanthera colubrina (Fabaceae). The nest web contained three main interaction modules: one composed by woodpeckers interacting with both living and standing dead trees; another by non-excavator birds using decay-formed cavities in living trees; and a third small module that had a few birds using woodpecker-excavated cavities in living trees. Important tree species were different for woodpecker and non-excavator modules. Extinction simulation of the most important tree species tripled the negative impact on cavity-using bird assemblage compared with the random extinction of tree species. In logging operations special consideration should be taken to ensure the maintenance of key tree species for the conservation of all the nest-web components in PF. [ABSTRACT FROM AUTHOR]

Over the last 34 years, Lake Müggelsee has experienced concurrent warming and nutrient reduction. While the effects of environmental change on single taxonomic or physical–chemical variables have been relatively well researched in isolation, understanding how environmental change propagates through the ecological network remains a major challenge. Capitalizing on the long-term monitoring program of the German Long-Term Ecosystem Research Network site Lake Müggelsee (1979-ongoing), we identified three time periods (1979–1995; 1996–2005; 2006–2013) which differed significantly in phytoplankton biomass and relative plankton community composition. Using multivariate first order autoregressive (MAR1) modeling on 13 pelagic plankton groups and four abiotic variables, we quantified interaction networks and indicators of stability and centrality for each period. Our results suggested that the Müggelsee network was bottom-up regulated in all periods and that stability increased over time. Moreover, in all three networks, non-trophic and indirect interactions appeared to be as commonly present as trophic and direct interactions. Using network centrality measures of betweenness and closeness, we identified keystone plankton groups and groups particularly responsive to environmental change based on variation in centrality ranks over time. Given a more comprehensive understanding of the interaction network at hand, MAR1 model-derived stability and centrality measures may potentially be used as integrated ecological indicators to monitor changes in stability of lake ecosystems and to identify particularly vulnerable components of the network. [ABSTRACT FROM AUTHOR]

Interaction networks ( IN ) have been used in ecology to model different kinds of interactions in ecological communities. Historically there are two basic ways to construct an IN : binary networks ( BN ) that represent unweighted links among species in the web, and weighted networks ( WN ) that weight each interaction among species by its relative or absolute frequency in the web. We call binary reduction the transition from WN to BN which obviously entails loss of information. We performed an analysis with 69 WN on which we worked the binary reduction. For both WN and BN we computed: the coefficient of variation, skewness, kurtosis, Shannon entropy and the Gini coefficient on the population statistics. We also computed the dependence asymmetry, the pairwise Jaccard distance and two different measures of nestedness, (W)NODF and τ -temperature, for the WN and BN . From correlations between the values for WN and BN we concluded that, for most of the indices, the loss of information due to the binary reduction is not significant. Using a statistical evaluation, for most indices, BN give similar results to their corresponding WN . [ABSTRACT FROM AUTHOR]

We discuss the relationship between two patterns found in interaction networks ( IN s) of community ecology: modularity and asymmetric specialisation. These two patterns express two opposite features: asymmetric specialisation suggests an interplay of generalists and specialists forming an entangled web of interconnected species, while modularity brings the idea of groups of species interacting in isolated cliques. We perform the analysis using Dependence Asymmetry ( DA ), which is the simplest way to quantify asymmetric specialisation. We construct an algorithm that finds the pattern of maximal DA , and we estimate the upper bound of DA analytically. We study the symmetric modular structure that has zero DA , and then force an asymmetric mismatch in this pattern to generate high DA , allowing us to compare it with a random pattern and with the maximal possible value. We conclude that, despite the opposite notions suggested by the studied patterns, if a modular pattern has enough asymmetry it resembles a specialised asymmetric pattern. [ABSTRACT FROM AUTHOR]

The tight interaction between somatic and germline cells is conserved in animal spermatogenesis. The testes of Drosophila melanogaster are the model of choice to identify processes responsible for mature gamete production. However, processes of differentiation and soma-germline interactions occurring in somatic cyst cells are currently understudied. Here we focused on the comparison of transcriptome expression patterns of early and mature somatic cyst cells to find out the developmental changes taking place in them. We employed a FACS-based approach for the isolation of early and mature somatic cyst cells from fly testes, subsequent preparation of RNA-Seq libraries, and analysis of gene differential expression in the sorted cells. We found increased expression of genes involved in cell cycle-related processes in early cyst cells, which is necessary for the proliferation and self-renewal of a crucial population of early cyst cells, cyst stem cells. Genes proposedly required for lamellipodium-like projection organization for proper cyst formation were also detected among the upregulated ones in early cyst cells. Gene Ontology and interactome analyses of upregulated genes in mature cyst cells revealed a striking over-representation of gene categories responsible for metabolic and catabolic cellular processes, as well as genes supporting the energetic state of the cells provided by oxidative phosphorylation that is carried out in mitochondria. Our comparative analyses of differentially expressed genes revealed major peculiarities in early and mature cyst cells and provide novel insight into their regulation, which is important for male fertility. • FACS-based protocol to isolate early and mature cyst cells from Drosophila testes. • Whole-transcriptome data from early and mature cyst cells and total testis samples. • Comparison of differentially expressed genes between early and mature cyst cells. • Uncovering stage-specific molecular complexes and processes in somatic cyst cells. [ABSTRACT FROM AUTHOR]

Abstract: Background and scope: Large networks, such as protein interaction networks, are extremely difficult to analyze as a whole. We developed Clust&See, a Cytoscape plugin dedicated to the identification, visualization and analysis of clusters extracted from such networks. Implementation and performance: Clust&See provides the ability to apply three different, recently developed graph clustering algorithms to networks and to visualize: (i) the obtained partition as a quotient graph in which nodes correspond to clusters and (ii) the obtained clusters as their corresponding subnetworks. Importantly, tools for investigating the relationships between clusters and vertices as well as their organization within the whole graph are supplied. [Copyright &y& Elsevier]

Highlights: [•] Large frugivores may be key as seed dispersers. [•] The loss of large frugivores can deeply affect seed-dispersal networks. [•] Large vertebrates are often absent from descriptions of seed-dispersal networks. [•] Possible causes are defaunation, taxonomic bias and secretive behavior. [•] We suggest an approach to assess the importance of large frugivores. [ABSTRACT FROM AUTHOR]

Abstract: Systems biology techniques are a topic of recent interest within the neurological field. Computational intelligence (CI) addresses this holistic perspective by means of consensus or ensemble techniques ultimately capable of uncovering new and relevant findings. In this paper, we propose the application of a CI approach based on ensemble Bayesian network classifiers and multivariate feature subset selection to induce probabilistic dependences that could match or unveil biological relationships. The research focuses on the analysis of high-throughput Alzheimer''s disease (AD) transcript profiling. The analysis is conducted from two perspectives. First, we compare the expression profiles of hippocampus subregion entorhinal cortex (EC) samples of AD patients and controls. Second, we use the ensemble approach to study four types of samples: EC and dentate gyrus (DG) samples from both patients and controls. Results disclose transcript interaction networks with remarkable structures and genes not directly related to AD by previous studies. The ensemble is able to identify a variety of transcripts that play key roles in other neurological pathologies. Classical statistical assessment by means of non-parametric tests confirms the relevance of the majority of the transcripts. The ensemble approach pinpoints key metabolic mechanisms that could lead to new findings in the pathogenesis and development of AD. [Copyright &y& Elsevier]

Abstract: We study a class of composed networks that are formed by two tree networks, and , whose end points touch each other through a bipartite network . We explore this network using a functional approach. We are interested in how much the topology, or the structure, of ( or ) determines the links of . This composed structure is a useful model in evolutionary biology, where and are the phylogenetic trees of plants and animals that interact in an ecological community. We make use of ecological networks of dispersion of fruits, which are formed by frugivorous animals and plants with fruits; the animals, usually birds, eat fruits and disperse their seeds. We analyse how the phylogeny of determines or is correlated with using a Monte Carlo approach. We use the phylogenetic distance among elements that interact with a given species to construct an index that quantifies the influence of over . The algorithm is based on the assumption that interaction matrices that follows a phylogeny of have a total phylogenetic distance smaller than the average distance of an ensemble of Monte Carlo realisations. We find that the effect of phylogeny of animal species is more pronounced in the ecological matrix than plant phylogeny. [Copyright &y& Elsevier]

Abstract: Aging is a multifactorial phenomenon, a multiscale process that takes place at the molecular (proteins, genes), cellular and tissue levels and represents a complex set of events. This review will focus on the databases related to the aging process and on aging-related biological networks recently constructed to decipher the molecular mechanisms of aging, to characterize the effects of environmental factors and calorie restriction on aging and to determine the molecular links between aging and several diseases. The role played by chaperones, that are major participants of aging cellular networks and connect metabolic stress and dietary restriction, and by microRNAs as modulators of aging are discussed. Given that higher proportions of predicted microRNA target sites exist in the transcripts encoding disordered proteins, and that intrinsically disordered proteins are associated with age-related diseases (cancer, diabetes, cardiovascular and neurodegenerative diseases), the study of protein disorder in aging deserves to be investigated. [Copyright &y& Elsevier]

Abstract: Allostery in the binding of peptides to DNA has been studied by quantitative DNase I footprinting using four newly designed peptides containing the XP(Hyp)RK motif and N-methylpyrrole (Py) moieties. Apparent binding constants in the micromolar range as well as Hill coefficients were determined for each peptide. The results, together with previous studies on five other peptides support the proposal that interaction network cooperativity is highly preferred in DNA–peptide interactions that involve multiple recognition sites. It is envisaged that interstrand bidentate interactions participate in the relay of conformational changes between recognition sites on the complementary strands. Models for interpreting DNA allostery based upon interaction networks are outlined. Circular dichroism experiments involving the titration of peptides against a short oligonucleotide duplex indicate that some of these peptides bind in a dimeric manner to DNA via the minor groove, inducing characteristic conformational changes. These insights should prompt the design of new DNA-binding peptides for investigating allosteric interactions between peptides and DNA, as well as novel interaction networks, and ultimately may shed light upon the fundamental chemical rules that govern allostery in more complex biological process such as DNA–protein interaction networks. [Copyright &y& Elsevier]

Abstract: A graph theoretical approach is applied to analyze the dynamic evolution of retention of carbon dioxide (CO2) molecules in single-walled carbon nanotubes (SWNTs). The trajectories of the molecules were obtained from the Molecular Dynamics (MD) simulations performed at constant temperature, T =300K, with a duration of 10ns. The simulation box contains four single-walled carbon nanotubes and 408 CO2 molecules with a bulk number density of 0.042nm−3. Non-bonding interaction distances between CO2 molecules during the simulation were calculated in 1ns intervals and these values were used to construct 10 dynamic interaction networks, by taking a cut-off value of 0.9nm for the van der Waals distance. Each of these interaction networks were then analyzed with the two global measures of graph theory: connectivity and clustering coefficient. Our results signified that an increase in the average clustering coefficient in corresponding networks is a reliable indicator for CO2 sequestration in single-walled carbon nanotubes. In addition, the distance distribution for each of the interaction networks revealed that the CO2 molecules retained in carbon nanotubes have a tendency to localize around a distance of 0.48nm. Consequently, the network representation of CO2 molecules and their encapsulation in SWNTs is in agreement with the actual MD simulation. In summary, the study presented here uses graph theoretical approach to interpret the results received from MD simulations providing a powerful tool to analyze such simulations. [Copyright &y& Elsevier]

• Between April 2014 to April 2015, 247 bats were captured in the municipality of Montes Claros, Minas Gerais, Brazil. • The overall infection rate of Leishmania spp. in bats was 4.4% (11/247). • Of the 11 bats infected, eight were of the Artibeus planirostris species. • Phylogenetic analysis classified the isolates from bats as: Leishmania (Viannia) sp. , L. (L.) infantum, L. (L.) amazonensis. • This is the first record of the bat Artibeus cinereus as a host of L. (L.) amazonensis. This study aimed to determine the occurrence of Leishmania infection in bats in urban and wild areas in an endemic municipality for visceral and cutaneous leishmaniasis in Minas Gerais, Brazil. Between April 2014 to April 2015, 247 bats were captured and classified into 26 species belonging to Phyllostomidae (90.7%), Vespertilionidae (8.1%) and Molossidae (1.2%) families. Blood samples from 247 bats were collected and submitted to nested-PCR, targeting the variable V7-V8 region of the SSU rRNA gene, followed by sequencing of the PCR product. The overall infection rate of Leishmania spp. in bats was 4.4%. Of the eleven bats infected, ten were frugivorous bats: Artibeus planirostris (8/11), Artibeus lituratus (1/11) and Artibeus cinereus (1/11) and one a nectarivorous bat (Glossophaga soricina). None of the individuals exhibited macroscopic alterations in the skin, spleen or liver. Phylogenetic analysis separated Leishmania species in clades corresponding to the subgenera Viannia, Leishmania , and Mundinia , and supported that the isolates characterized in the present study clustered closely with Leishmania (Viannia) sp., Leishmania (Leishmania) infantum and Leishmania (Leishmania) amazonensis. Here we report for the first time the bat Artibeus cinereus as a host of Leishmania (Leishmania) amazonensis. In the study we found that the mean abundance of bats did not differ in wild habitats and urban areas and that bat-parasite interactions were similarly distributed in the two environments. On the other hand, further studies should be conducted in more recent times to verify whether there have been changes in these parameters. [ABSTRACT FROM AUTHOR]

Memetic algorithms are known for their enhanced solution refinement capabilities. These capabilities are a result of incorporating local-search methods into population-based metaheuristics such as swarm and evolutionary algorithms. However, designing a memetic algorithm is not a trivial task. The inclusion of local-search procedures must consider the exploitation–exploration balance and its interplay with other algorithm operators. Due to these variables, there is no universal methodology to design a memetic algorithm. Although previous works have investigated the impact of local search procedures on genetic and ant colony algorithms, we have limited knowledge about the impact of these procedures on other types of swarm-based algorithms. For swarm-based algorithms, the interactions within the population are vital to the emergence of collective intelligence and shape the algorithm's behaviour. Here, we model these interactions into a network and analyse the impact of local search in swarm-based algorithms. We selected the Particle Swarm Optimization (PSO), the Artificial Bee Colony (ABC), and one memetic version of each algorithm as a case study. We examined the effects of the modifications proposed in the memetic variants. The results obtained indicate that the networks of interactions capture several characteristics of the algorithms and the impact of the local search strategies. The impact of local search operators can be gauged by the temporal analysis of the changes in the structural properties of the algorithm's network (e.g. study of the weight and distribution of the network's connections). These changes are linked to the algorithms' convergence signature and can be used as a proxy to assess the differences between the algorithms studied and their memetic versions. [ABSTRACT FROM AUTHOR]

On July 16, 2010, a pipeline explosion spilled 1500 tons of crude oil into the Port of Dalian, China. To identify taxa responses to the spill, we exploited seven years of monitoring data to examine the co-occurrence of taxon pairs and the variation of the macrobenthic community. Non-parametric correlation analysis was used to construct interaction networks of relationships between oil spill contaminants and macrobenthic taxa. We observed that the impacted macrobenthic community not restored before 2016. The tolerance/sensitivity of taxa was inconsistent with the studies of oil impacts in other locations. We suggest revision of the ecological group classification of Sabellidae, Lumbrineridae, Terebellidae, Sternaspidae, and Spionidae. The variation in the frequency of coexistence indicates the potential impact of oil spill pollution on resource occupation. The interaction network involving macrobenthic families and stressors associated with the oil spill highlights how different macrobenthic families respond to different combinations of stressors. • The Macrobenthic community structure impacted by Dalian Bay oil spill not restored until 2016. • The tolerance/sensitivity of some taxa in this study was inconsistent with other locations. • The variation in taxa coexistence indicates the potential impact of oil spill pollution on resource occupation. • The interaction network highlights how different macrobenthic families respond to different combinations of stressors. [ABSTRACT FROM AUTHOR]

• Under high NH 4 NO 3 availability, paddy soils with 125% WFPS produced the highest N 2 O. • Denitrification was the dominant process to N 2 O flux during rice growing seasons. • A few key taxa of nirK - and nosZ -containing denitrifiers mitigate N 2 O emissions. Debate persists regarding the underlying factors influencing nitrous oxide (N 2 O) emissions and their mechanisms of action in rice paddy soils. The aim of the present study was to delineate the contributions of nitrification and denitrification to N 2 O emissions in acidic paddy soils under adequate N fertilisation. To identify the key taxa associated with N 2 O emissions and explore the potential underlying mechanisms, we performed stable N isotope (15N) tracing, quantitative PCR, and Illumina MiSeq sequencing of amoA , nirK , nirS, and nosZ genes. Under sufficient NH 4 NO 3 input, soil N 2 O emissions increased significantly with an increase in soil moisture, peaking at 125% water-filled pore space (WFPS). N 2 O flux was positively associated with potential denitrification rates but not potential nitrification rates. The relative contribution of denitrification to N 2 O emissions increased with an increase in soil moisture and reached more than 90% at 75%, 100%, and 125% WFPS during the 96 h of incubation. Based on relative abundance and connectivity degree of operational taxonomic units, soil moisture-enhanced N 2 O emissions were strongly correlated with only a few key taxa, including nirK -containing denitrifiers belonging to Bradyrhizobium , as well as nosZ -containing denitrifiers belonging to Tardiphaga. In conclusion, denitrification could play a more dominant role in N 2 O emissions than nitrification in acidic paddy soil under sufficient NH 4 NO 3 inputs, and the effects of soil moisture on N 2 O emissions could be attributed to a few key nirK - and nosZ -denitrifier taxa, through shifts in community composition and synergistic interactions of network structures between them. [ABSTRACT FROM AUTHOR]

Proteoglycans (PGs) represent a large proportion of the components that constitute the extracellular matrix (ECM). They are a diverse group of glycoproteins characterized by a covalent link to a specific glycosaminoglycan type. As part of the ECM, heparan sulfate (HS)PGs participate in both physiological and pathological processes including cell recruitment during inflammation and the promotion of cell proliferation, adhesion and motility during development, angiogenesis, wound repair and tumor progression. A key function of HSPGs is their ability to modulate the expression and function of cytokines, chemokines, growth factors, morphogens, and adhesion molecules. This is due to their capacity to act as ligands or co-receptors for various signal-transducing receptors, affecting pathways such as FGF, VEGF, chemokines, integrins, Wnt, notch, IL-6/JAK-STAT3, and NF-κB. The activation of those pathways has been implicated in the induction, progression, and malignancy of a tumor. For many years, the study of signaling has allowed for designing specific drugs targeting these pathways for cancer treatment, with very positive results. Likewise, HSPGs have become the subject of cancer research and are increasingly recognized as important therapeutic targets. Although they have been studied in a variety of preclinical and experimental models, their mechanism of action in malignancy still needs to be more clearly defined. In this review, we discuss the role of cell-surface HSPGs as pleiotropic modulators of signaling in cancer and identify them as promising markers and targets for cancer treatment. [ABSTRACT FROM AUTHOR]

• Plant-solitary bee networks have a stable core but a variable periphery. • Osmia caerulescens is a good bioindicator of management types. • Osmia bicornis is a good bioindicator of ecosystem recovery. • Aboveground cavity-nesting bees pollinate many wild herb plants in olive orchards. • Plant species identified at the core are of conservation priority for bees. The identification of important nodes structuring pollination networks represents a key contribution to biodiversity conservation and pollination functioning. Understanding how species and their importance covary with management is essential if we aim to predict anthropic effects on the environment. In this study we used 96 bee trap nests to sample plant (pollen)-solitary bee interaction networks in 18 pairs of olive groves employing differing management techniques (intensive vs. organic). We applied a novel dual analytical approach consisting of identifying important nodes from two different perspectives: nodes that strongly determine the topological structure of the network and nodes that sustain rare or infrequent interactions. We employed this analytical approach to identify important nodes for the conservation of these networks and to study how different agricultural management practices modify the importance of the nodes. Specifically, Osmia caerulescens appeared in the core of the network of organic farms and acts as a good bioindicator of agricultural management types. As well, O. bicornis participated in important singular interactions but only on organic farms and so can be considered as a good bioindicator of ecosystem recovery. Our results highlight the species that should be prioritized for conservation or restoration and reveal a core-periphery structure in networks, in which, despite most structuring species remaining constant across management types, certain important singular interactions differ. We demonstrate that the switch from intensive to organic farming on olive farms can restore the structure of these plant-solitary bee networks, mainly through the recovery of certain species and rare or infrequent interactions. [ABSTRACT FROM AUTHOR]

• Our transcriptome analysis of a PD mouse model revealed differences in gene expression patterns in the CC, HP, ST, and CB. • The possible DEGs involved in PD were Lrrk2 , Mtor , Gxylt1 , C920006o11Rik , Vdac1 , Drd4 , and Ncan. • Based on functional enrichment of DEGs in different brain regions, it appears that the HP and ST are dominant in the occurrence of PD, while the CB and CC also play a role in the regulation of PD pathology. Parkinson's disease (PD) is the second most common neurodegenerative disease. However, the expression pattern and the differential gene in different brain regions and its functions remain unclear although many studies have been reported. In this present study, PD mouse model were build and four brain regions (cerebral cortex: CC, hippocampus: HP, striatum: ST, and cerebellum: CB) were separated for RNA-seq analysis. Results showed that different expressed genes were found between the different brain regions and more differential genes found in ST and HP when compared with control groups. Among them, Lrrk2 , Mtor , Gxylt1 , C920006o11Rik , Vdac1 , Drd4 , and Ncan showed the most significant to PD. PDCC vs. PDHP, PDHP vs. PDST and PDCC vs. PDST groups have 334, 722 and 495 differentially expressed genes (DEGs), respectively. Functional analyses results showed that the differential genes mainly related with posttranscriptional regulation of gene expression and protein localization to organelle and so on, which involved in AMPK, PI3K-Akt signaling pathway, and GABA-ergic synapse. Network biology analysis showed LRRK2, DRD2, IGF-1, GNAI1, GNAI3, PRKACA, PPP2R5C, and PIK3R1 play a major role in protein regulation of PD. Therefore, HP and ST play more important roles in the development of PD and it is also suggested the potential target gene for diagnosis and treatment of PD. [ABSTRACT FROM AUTHOR]