Network, degeneracy and bow tie. Integrating paradigms and architectures to grasp the complexity of the immune system

Endless forms of endless formation - The morphogenesis of organisms and scientific objects

The present article proceeds from the premises that living forms and abstract formalization come into being by similar mechanisms (e.g., random variation, selection, conventions) and have similar properties (e.g., semiosis, stasis and complexity). These convergences justify the comparative analysis of form's development, evolution and action in both fields. Here we shall focus on the notion of "endless forms" advanced by Darwin's seminal work in evolutionary biology "On The Origin of Species" to discuss the various ways in which it relates to biological formation. I shall explore the idea of "infinitude of evolved forms" through the lens of the five connotations of the word "endless" provided by the Merriam-Webster Thesaurus dictionary, which are: perpetual; incomputable; manifold; unfinished; steady. From each synonym chosen, a new iteration of dictionary search was made to produce a list of terms that are used in the reviewed literature to describe biological morphogenetic features, which are respectively: reproducible, unpredictable, additive, undetermined, the end of their own formation. In conclusion, I propose a tentative mapping between each of these five connotations and the biological processes at work in their making, which are, respectively: 1) copying organic information; coding organic signs; manufacturing organic meaning 2) natural variation, natural selection, natural conventions; 3) multilevel organization, differentiation/development, complexity; 4) ambiguity, degeneracy, semiotic thresholds; 5) homeostasis, autopoiesis, codepoiesis. The processes discussed here gained salience as developments, additions, or nuances to Darwin's original theory. It must be noted that, even though the discussion is mainly framed by Code Biology as a source of conceptualization, inputs from a wide range of theoretical perspectives will be given emphasis when suitable.

Meta-Inflammation and New Anti-Diabetic Drugs: A New Chance to Knock Down Residual Cardiovascular Risk

Type 2 diabetes mellitus (DM) represents, with its macro and microvascular complications, one of the most critical healthcare issues for the next decades. Remarkably, in the context of regulatory approval trials, sodium-glucose cotransporter 2 inhibitors (SGLT2i) and glucagon-like peptide 1 receptor agonists (GLP-1 RAs) proved a reduced incidence of major adverse cardiovascular events (MACEs), i.e., cardiovascular death and heart failure (HF) hospitalizations. The cardioprotective abilities of these new anti-diabetic drugs seem to run beyond mere glycemic control, and a growing body of evidence disclosed a wide range of pleiotropic effects. The connection between diabetes and meta-inflammation seems to be the key to understanding how to knock down residual cardiovascular risk, especially in this high-risk population. The aim of this review is to explore the link between meta-inflammation and diabetes, the role of newer glucose-lowering medications in this field, and the possible connection with their unexpected cardiovascular benefits.

Bow-tie architectures in biological and artificial neural networks: Implications for network evolution and assay design

Modern artificial neural networks (ANNs) have long been designed on foundations of mathematics as opposed to their original foundations of biomimicry. However, the structure and function of these modern ANNs are often analogous to real-life biological networks. We propose that the ubiquitous information-theoretic principles underlying the development of ANNs are similar to the principles guiding the macro-evolution of biological networks and that insights gained from one field can be applied to the other. We generate hypotheses on the bow-tie network structure of the Janus kinase - signal transducers and activators of transcription (JAK-STAT) pathway, additionally informed by the evolutionary considerations, and carry out ANN simulation experiments to demonstrate that an increase in the network's input and output complexity does not necessarily require a more complex intermediate layer. This observation should guide novel biomarker discovery-namely, to prioritize sections of the biological networks in which information is most compressed as opposed to biomarkers representing the periphery of the network.

Data structuring may prevent ambiguity and improve personalized medical prognosis

Topics expected to influence personalized medicine (PM), where medical decisions, practices, and treatments are tailored to the individual patient, are reviewed. Lack of discrimination due to different biological conditions that express similar values of numerical variables (ambiguity) is regarded to be a major potential barrier for PM. This material explores possible causes and sources of ambiguity and offers suggestions for mitigating the impacts of uncertainties. Three causes of ambiguity are identified: (1) delayed adoption of innovations, (2) inadequate emphases, and (3) inadequate processes used when new medical practices are developed and validated. One example of the first problem is the relative lack of medical research on "compositional data" -the type that characterizes leukocyte data. This omission results in erroneous use of data abundantly utilized in medicine, such as the blood cell differential. Emphasis on data output ‒not biomedical interpretation that facilitates the use of clinical data‒ exemplifies the second type of problems. Reliance on tools generated in other fields (but not validated within biomedical contexts) describes the last limitation. Because reductionism is associated with these problems, non-reductionist alternatives are reviewed as potential remedies. Data structuring (converting data into information) is considered a key element that may promote PM. To illustrate a process that includes data-information-knowledge and decision-making, previously published data on COVID-19 are utilized. It is suggested that ambiguity may be prevented or ameliorated. Provided that validations are grounded on biomedical knowledge, approaches that describe certain criteria - such as non-overlapping data intervals of patients that experience different outcomes, immunologically interpretable data, and distinct graphic patterns - can inform, at personalized bases, earlier and/or with fewer observations.

A complex systems approach to aging biology

Having made substantial progress understanding molecules, cells, genes and pathways, aging biology research is now moving toward integration of these parts, attempting to understand how their joint dynamics may contribute to aging. Such a shift of perspective requires the adoption of a formal complex systems framework, a transition being facilitated by large-scale data collection and new analytical tools. Here, we provide a theoretical framework to orient researchers around key concepts for this transition, notably emergence, interaction networks and resilience. Drawing on evolutionary theory, network theory and principles of homeostasis, we propose that organismal function is accomplished by the integration of regulatory mechanisms at multiple hierarchical scales, and that the disruption of this ensemble causes the phenotypic and functional manifestations of aging. We present key examples at scales ranging from sub-organismal biology to clinical geriatrics, outlining how this approach can potentially enrich our understanding of aging.

The Role of Immunosenescence in Cerebral Small Vessel Disease: A Review

Cerebral small vessel disease (CSVD) is one of the most important causes of vascular dementia. Immunosenescence and inflammatory response, with the involvement of the cerebrovascular system, constitute the basis of this disease. Immunosenescence identifies a condition of deterioration of the immune organs and consequent dysregulation of the immune response caused by cellular senescence, which exposes older adults to a greater vulnerability. A low-grade chronic inflammation status also accompanies it without overt infections, an “inflammaging” condition. The correlation between immunosenescence and inflammaging is fundamental in understanding the pathogenesis of age-related CSVD (ArCSVD). The production of inflammatory mediators caused by inflammaging promotes cellular senescence and the decrease of the adaptive immune response. Vice versa, the depletion of the adaptive immune mechanisms favours the stimulation of the innate immune system and the production of inflammatory mediators leading to inflammaging. Furthermore, endothelial dysfunction, chronic inflammation promoted by senescent innate immune cells, oxidative stress and impairment of microglia functions constitute, therefore, the framework within which small vessel disease develops: it is a concatenation of molecular events that promotes the decline of the central nervous system and cognitive functions slowly and progressively. Because the causative molecular mechanisms have not yet been fully elucidated, the road of scientific research is stretched in this direction, seeking to discover other aberrant processes and ensure therapeutic tools able to enhance the life expectancy of people affected by ArCSVD. Although the concept of CSVD is broader, this manuscript focuses on describing the neurobiological basis and immune system alterations behind cerebral aging. Furthermore, the purpose of our work is to detect patients with CSVD at an early stage, through the evaluation of precocious MRI changes and serum markers of inflammation, to treat untimely risk factors that influence the burden and the worsening of the cerebral disease.

GDF15, an emerging key player in human aging

Growth differentiation factor 15 (GDF15) is recently emerging not only as a stress-related mitokine, but also as a key player in the aging process, being one of the most up-regulated protein with age and associated with a variety of age-related diseases (ARDs). Many data indicate that GDF15 has protective roles in several tissues during different stress and aging, thus playing a beneficial role in apparent contrast with the observed association with many ARDs. A possible detrimental role for this protein is then hypothesized to emerge with age. Therefore, GDF15 can be considered as a pleiotropic factor with beneficial activities that can turn detrimental in old age possibly when it is chronically elevated. In this review, we summarize the current knowledge on the biology of GDF15 during aging. We also propose GDF15 as a part of a dormancy program, where it may play a role as a mediator of defense processes aimed to protect from inflammatory damage and other stresses, according to the life history theory.

Multi-Cellular Immunological Interactions Associated With COVID-19 Infections

To rapidly prognosticate and generate hypotheses on pathogenesis, leukocyte multi-cellularity was evaluated in SARS-CoV-2 infected patients treated in India or the United States (152 individuals, 384 temporal observations). Within hospital (<90-day) death or discharge were retrospectively predicted based on the admission complete blood cell counts (CBC). Two methods were applied: (i) a "reductionist" one, which analyzes each cell type separately, and (ii) a "non-reductionist" method, which estimates multi-cellularity. The second approach uses a proprietary software package that detects distinct data patterns generated by complex and hypothetical indicators and reveals each data pattern's immunological content and associated outcome(s). In the Indian population, the analysis of isolated cell types did not separate survivors from non-survivors. In contrast, multi-cellular data patterns differentiated six groups of patients, including, in two groups, 95.5% of all survivors. Some data structures revealed one data point-wide line of observations, which informed at a personalized level and identified 97.8% of all non-survivors. Discovery was also fostered: some non-survivors were characterized by low monocyte/lymphocyte ratio levels. When both populations were analyzed with the non-reductionist method, they displayed results that suggested survivors and non-survivors differed immunologically as early as hospitalization day 1.

Two theories of action - Edelman's Neuronal group Selection and the Poetics of Paul Valéry

Motivated by two imperatives as they are framed in Code Biology - mechanism and actualization - we have turned to other attempts of modeling life at work. Here, we present two theories devoted to minds in action - one explains neuronal function, and the other dissects poetic crafting. Neuronal networks activation and poetic composition, respectively, are seen as the selection of specific connective patterns of either neurons or words, in action. Gerald Edelman, as a scientist, has generalized the Darwinian ideas of variation and selection to the cellular level in his "Sciences of Recognition", a broader theoretical framework that includes the "Theory of Neuronal Group Selection" (TGNS) analyzed here. Paul Valéry, as a poet, has reconciled inspiration and technique in what he has called "works of the mind", the creative processes mediated by sensing and making sense, in the "Poetic Theory" we present here he advances the mechanisms of artistic composition. We have identified the main ideas conveyed in these two theories, i.e., variation and selection, integration and differentiation, ambiguity and degeneracy, binding and blending, stasis and semiosis, by pairing and comparing textual fragments from the authors. We show that TGNS and the Theory of Poetic Action reconcile Sciences and Arts by recognizing that Natural Selection is a mechanism implied by formative acts in both scenarios and discuss to which extent Natural Convention - the main contribution of Code Biology - is integrated by the two thinkers.

The Use of a Game Theory Model to Explore the Emergence of Core/Periphery Structure in Networks and Its Symmetry

In network systems characterized by complex interactions of various types, core-periphery structures can be found. In this paper, we deal with such questions as what processes can lead to the emergence of core-periphery formation, whether this structure is symmetric, and to what extent. Namely, the question of symmetry in a complex network is still the subject of intense research interest. Symmetry can relate to network topology, network relationships, and other processes on networks. To answer these questions, we modified the model of the classic social dilemma called the repeated prisoner’s dilemma (or repeated PD game) by adding the cost of maintaining relationships between the pairs of players (partners) and especially by adding the possibility of ending some relationships. We present the results of simulations that suggest that the players’ network strategy (i.e., partner selection or termination of relationships with some partners) is the driving force behind the emergence of a core-periphery structure in networks rather than the player’s strategy in PD. Our results also suggest that the formed core is symmetric, and this symmetry is a result of the symmetric interactions of core players. Our outcomes can help understand various economic or social questions related to creating centers or peripheries, including their symmetry in different network systems.

Robust Physiological Metrics From Sparsely Sampled Networks

Physiological and biochemical networks are highly complex, involving thousands of nodes as well as a hierarchical structure. True network structure is also rarely known. This presents major challenges for applying classical network theory to these networks. However, complex systems generally share the property of having a diffuse or distributed signal. Accordingly, we should predict that system state can be robustly estimated with sparse sampling, and with limited knowledge of true network structure. In this review, we summarize recent findings from several methodologies to estimate system state via a limited sample of biomarkers, notably Mahalanobis distance, principal components analysis, and cluster analysis. While statistically simple, these methods allow novel characterizations of system state when applied judiciously. Broadly, system state can often be estimated even from random samples of biomarkers. Furthermore, appropriate methods can detect emergent underlying physiological structure from this sparse data. We propose that approaches such as these are a powerful tool to understand physiology, and could lead to a new understanding and mapping of the functional implications of biological variation.

Genomic Variation, Evolvability, and the Paradox of Mental Illness

Twentieth-century genetics was hard put to explain the irregular behavior of neuropsychiatric disorders. Autism and schizophrenia defy a principle of natural selection; they are highly heritable but associated with low reproductive success. Nevertheless, they persist. The genetic origins of such conditions are confounded by the problem of variable expression, that is, when a given genetic aberration can lead to any one of several distinct disorders. Also, autism and schizophrenia occur on a spectrum of severity, from mild and subclinical cases to the overt and disabling. Such irregularities reflect the problem of missing heritability; although hundreds of genes may be associated with autism or schizophrenia, together they account for only a small proportion of cases. Techniques for higher resolution, genomewide analysis have begun to illuminate the irregular and unpredictable behavior of the human genome. Thus, the origins of neuropsychiatric disorders in particular and complex disease in general have been illuminated. The human genome is characterized by a high degree of structural and behavioral variability: DNA content variation, epistasis, stochasticity in gene expression, and epigenetic changes. These elements have grown more complex as evolution scaled the phylogenetic tree. They are especially pertinent to brain development and function. Genomic variability is a window on the origins of complex disease, neuropsychiatric disorders, and neurodevelopmental disorders in particular. Genomic variability, as it happens, is also the fuel of evolvability. The genomic events that presided over the evolution of the primate and hominid lineages are over-represented in patients with autism and schizophrenia, as well as intellectual disability and epilepsy. That the special qualities of the human genome that drove evolution might, in some way, contribute to neuropsychiatric disorders is a matter of no little interest.

Neuro-Clinical Signatures of Language Impairments: A Theoretical Framework for Function-to-structure Mapping in Clinics

In the past decades, neuroscientists and clinicians have collected a considerable amount of data and drastically increased our knowledge about the mapping of language in the brain. The emerging picture from the accumulated knowledge is that there are complex and combinatorial relationships between language functions and anatomical brain regions. Understanding the underlying principles of this complex mapping is of paramount importance for the identification of the brain signature of language and Neuro-Clinical signatures that explain language impairments and predict language recovery after stroke. We review recent attempts to addresses this question of language-brain mapping. We introduce the different concepts of mapping (from diffeomorphic one-to-one mapping to many-to-many mapping). We build those different forms of mapping to derive a theoretical framework where the current principles of brain architectures including redundancy, degeneracy, pluri-potentiality and bow-tie network are described.

Targeting Impaired Antimicrobial Immunity in the Brain for the Treatment of Alzheimer's Disease

Alzheimer's disease (AD) is the most common form of dementia and aging is the most common risk factor for developing the disease. The etiology of AD is not known but AD may be considered as a clinical syndrome with multiple causal pathways contributing to it. The amyloid cascade hypothesis, claiming that excess production or reduced clearance of amyloid-beta (Aβ) and its aggregation into amyloid plaques, was accepted for a long time as the main cause of AD. However, many studies showed that Aβ is a frequent consequence of many challenges/pathologic processes occurring in the brain for decades. A key factor, sustained by experimental data, is that low-grade infection leading to production and deposition of Aβ, which has antimicrobial activity, precedes the development of clinically apparent AD. This infection is chronic, low grade, largely clinically silent for decades because of a nearly efficient antimicrobial immune response in the brain. A chronic inflammatory state is induced that results in neurodegeneration. Interventions that appear to prevent, retard or mitigate the development of AD also appear to modify the disease. In this review, we conceptualize further that the changes in the brain antimicrobial immune response during aging and especially in AD sufferers serve as a foundation that could lead to improved treatment strategies for preventing or decreasing the progression of AD in a disease-modifying treatment.

Age-related cerebral small vessel disease and inflammaging

The continued increase in global life expectancy predicts a rising prevalence of age-related cerebral small vessel diseases (CSVD), which requires a better understanding of the underlying molecular mechanisms. In recent years, the concept of "inflammaging" has attracted increasing attention. It refers to the chronic sterile low-grade inflammation in elderly organisms and is involved in the development of a variety of age-related chronic diseases. Inflammaging is a long-term result of chronic physiological stimulation of the immune system, and various cellular and molecular mechanisms (e.g., cellular senescence, immunosenescence, mitochondrial dysfunction, defective autophagy, metaflammation, gut microbiota dysbiosis) are involved. With the deepening understanding of the etiological basis of age-related CSVD, inflammaging is considered to play an important role in its occurrence and development. One of the most critical pathophysiological mechanisms of CSVD is endothelium dysfunction and subsequent blood-brain barrier (BBB) leakage, which gives a clue in the identification of the disease by detecting circulating biological markers of BBB disruption. The regional analysis showed blood markers of vascular inflammation are often associated with deep perforating arteriopathy (DPA), while blood markers of systemic inflammation appear to be associated with cerebral amyloid angiopathy (CAA). Here, we discuss recent findings in the pathophysiology of inflammaging and their effects on the development of age-related CSVD. Furthermore, we speculate the inflammaging as a potential target for future therapeutic interventions to delay or prevent the progression of the age-related CSVD.

Degeneracy and Complexity in Neuro-Behavioral Correlates of Team Coordination

Team coordination-members of a group acting together rather than performing specific actions individually-is essential for success in many real-world tasks such as military missions, sports, workplace, or school interactions. However, team coordination is highly variable, which is one reason why its underlying neural processes are largely unknown. Here we used dual electroencephalography (EEG) in dyads to study the neurobehavioral dynamics of team coordination in an ecologically valid task that places intensive demands on joint performance. We present a novel conceptual framework to interpret neurobehavioral variability in terms of degeneracy, a fundamental property of complex biological systems said to enhance flexibility and robustness. We characterize degeneracy conceptually in terms of a manifold representing the geometric locus of the dynamics in the high dimensional state-space of neurobehavioral signals. The geometry and dimensionality of the manifold are determined by task constraints and team coordination requirements which restrict the manifold to trajectories that are conducive to successful task performance. Our results indicate that team coordination is associated with dimensionality reduction of the manifold as evident in increased inter-brain phase coherence of beta and gamma rhythms during critical phases of task performance where subjects exchange information. Team coordination was also found to affect the shape of the manifold manifested as a symmetry breaking of centro-parietal wavelet power patterns across subjects in trials with high team coordination. These results open a conceptual and empirical path to identifying the mechanisms underlying team performance in complex tasks.

Complete Topological Mapping of a Cellular Protein Interactome Reveals Bow-Tie Motifs as Ubiquitous Connectors of Protein Complexes

The network topology of a protein interactome is shaped by the function of each protein, making it a resource of functional knowledge in tissues and in single cells. Today, this resource is underused, as complete network topology characterization has proved difficult for large protein interactomes. We apply a matrix visualization and decoding approach to a physical protein interactome of a dendritic cell, thereby characterizing its topology with no prior assumptions of structure. We discover 294 proteins, each forming topological motifs called "bow-ties" that tie together the majority of observed protein complexes. The central proteins of these bow-ties have unique network properties, display multifunctional capabilities, are enriched for essential proteins, and are widely expressed in other cells and tissues. Collectively, the bow-tie motifs are a pervasive and previously unnoted topological trend in cellular interactomes. As such, these results provide fundamental knowledge on how intracellular protein connectivity is organized and operates.

The Role of PTEN in Innate and Adaptive Immunity

The lipid and protein phosphatase and tensin homolog (PTEN) controls the differentiation and activation of multiple immune cells. PTEN acts downstream from T- and B-cell receptors, costimulatory molecules, cytokine receptors, integrins, and also growth factor receptors. Loss of PTEN activity in human and mice is associated with cellular and humoral immune dysfunction, lymphoid hyperplasia, and autoimmunity. Although most patients with PTEN hamartoma tumor syndrome (PHTS) have no immunological symptoms, a subclinical immune dysfunction is present in many, and clinical immunodeficiency in few. Comparison of the immune phenotype caused by PTEN haploinsufficiency in PHTS, phosphoinositide 3-kinase (PI3K) gain-of-function in activated PI3K syndrome, and mice with conditional biallelic Pten deletion suggests a threshold model in which coordinated activity of several phosphatases control the PI3K signaling in a cell-type-specific manner. Emerging evidence highlights the role of PTEN in polygenic autoimmune disorders, infection, and the immunological response to cancer. Targeting the PI3K axis is an emerging therapeutic avenue.

Emergence of Hierarchical Modularity in Evolving Networks Uncovered by Phylogenomic Analysis

Networks describe how parts associate with each other to form integrated systems which often have modular and hierarchical structure. In biology, network growth involves two processes, one that unifies and the other that diversifies. Here, we propose a biphasic (bow-tie) theory of module emergence. In the first phase, parts are at first weakly linked and associate variously. As they diversify, they compete with each other and are often selected for performance. The emerging interactions constrain their structure and associations. This causes parts to self-organize into modules with tight linkage. In the second phase, variants of the modules diversify and become new parts for a new generative cycle of higher level organization. The paradigm predicts the rise of hierarchical modularity in evolving networks at different timescales and complexity levels. Remarkably, phylogenomic analyses uncover this emergence in the rewiring of metabolomic and transcriptome-informed metabolic networks, the nanosecond dynamics of proteins, and evolving networks of metabolism, elementary functionomes, and protein domain organization.

Inflammaging: a new immune-metabolic viewpoint for age-related diseases

Ageing and age-related diseases share some basic mechanistic pillars that largely converge on inflammation. During ageing, chronic, sterile, low-grade inflammation - called inflammaging - develops, which contributes to the pathogenesis of age-related diseases. From an evolutionary perspective, a variety of stimuli sustain inflammaging, including pathogens (non-self), endogenous cell debris and misplaced molecules (self) and nutrients and gut microbiota (quasi-self). A limited number of receptors, whose degeneracy allows them to recognize many signals and to activate the innate immune responses, sense these stimuli. In this situation, metaflammation (the metabolic inflammation accompanying metabolic diseases) is thought to be the form of chronic inflammation that is driven by nutrient excess or overnutrition; metaflammation is characterized by the same mechanisms underpinning inflammaging. The gut microbiota has a central role in both metaflammation and inflammaging owing to its ability to release inflammatory products, contribute to circadian rhythms and crosstalk with other organs and systems. We argue that chronic diseases are not only the result of ageing and inflammaging; these diseases also accelerate the ageing process and can be considered a manifestation of accelerated ageing. Finally, we propose the use of new biomarkers (DNA methylation, glycomics, metabolomics and lipidomics) that are capable of assessing biological versus chronological age in metabolic diseases.

Calcium as a signal integrator in developing epithelial tissues

Decoding how tissue properties emerge across multiple spatial and temporal scales from the integration of local signals is a grand challenge in quantitative biology. For example, the collective behavior of epithelial cells is critical for shaping developing embryos. Understanding how epithelial cells interpret a diverse range of local signals to coordinate tissue-level processes requires a systems-level understanding of development. Integration of multiple signaling pathways that specify cell signaling information requires second messengers such as calcium ions. Increasingly, specific roles have been uncovered for calcium signaling throughout development. Calcium signaling regulates many processes including division, migration, death, and differentiation. However, the pleiotropic and ubiquitous nature of calcium signaling implies that many additional functions remain to be discovered. Here we review a selection of recent studies to highlight important insights into how multiple signals are transduced by calcium transients in developing epithelial tissues. Quantitative imaging and computational modeling have provided important insights into how calcium signaling integration occurs. Reverse-engineering the conserved features of signal integration mediated by calcium signaling will enable novel approaches in regenerative medicine and synthetic control of morphogenesis.

Immunosenescence and Inflamm-Aging As Two Sides of the Same Coin: Friends or Foes?

The immune system is the most important protective physiological system of the organism. It has many connections with other systems and is, in fact, often considered as part of the larger neuro–endocrine–immune axis. Most experimental data on immune changes with aging show a decline in many immune parameters when compared to young healthy subjects. The bulk of these changes is termed immunosenescence. Immunosenescence has been considered for some time as detrimental because it often leads to subclinical accumulation of pro-inflammatory factors and inflamm-aging. Together, immunosenescence and inflamm-aging are suggested to stand at the origin of most of the diseases of the elderly, such as infections, cancer, autoimmune disorders, and chronic inflammatory diseases. However, an increasing number of immune-gerontologists have challenged this negative interpretation of immunosenescence with respect to its significance in aging-related alterations of the immune system. If one considers these changes from an evolutionary perspective, they can be viewed preferably as adaptive or remodeling rather than solely detrimental. Whereas it is conceivable that global immune changes may lead to various diseases, it is also obvious that these changes may be needed for extended survival/longevity. Recent cumulative data suggest that, without the existence of the immunosenescence/inflamm-aging duo (representing two sides of the same phenomenon), human longevity would be greatly shortened. This review summarizes recent data on the dynamic reassessment of immune changes with aging. Accordingly, attempts to intervene on the aging immune system by targeting its rejuvenation, it may be more suitable to aim to maintain general homeostasis and function by appropriately improving immune-inflammatory-functions.

Immunobiography and the Heterogeneity of Immune Responses in the Elderly: A Focus on Inflammaging and Trained Immunity

Owing to its memory and plasticity, the immune system (IS) is capable of recording all the immunological experiences and stimuli it was exposed to. The combination of type, dose, intensity, and temporal sequence of antigenic stimuli that each individual is exposed to has been named “immunobiography.” This immunological history induces a lifelong continuous adaptation of the IS, which is responsible for the capability to mount strong, weak or no response to specific antigens, thus determining the large heterogeneity of immunological responses. In the last years, it is becoming clear that memory is not solely a feature of adaptive immunity, as it has been observed that also innate immune cells are provided with a sort of memory, dubbed “trained immunity.” In this review, we discuss the main characteristics of trained immunity as a possible contributor to inflammaging within the perspective of immunobiography, with particular attention to the phenotypic changes of the cell populations known to be involved in trained immunity. In conclusion, immunobiography emerges as a pervasive and comprehensive concept that could help in understanding and interpret the individual heterogeneity of immune responses (to infections and vaccinations) that becomes particularly evident at old age and could affect immunosenescence and inflammaging.

Nature and Consequences of Biological Reductionism for the Immunological Study of Infectious Diseases

Evolution has conserved "economic" systems that perform many functions, faster or better, with less. For example, three to five leukocyte types protect from thousands of pathogens. To achieve so much with so little, biological systems combine their limited elements, creating complex structures. Yet, the prevalent research paradigm is reductionist. Focusing on infectious diseases, reductionist and non-reductionist views are here described. The literature indicates that reductionism is associated with information loss and errors, while non-reductionist operations can extract more information from the same data. When designed to capture one-to-many/many-to-one interactions-including the use of arrows that connect pairs of consecutive observations-non-reductionist (spatial-temporal) constructs eliminate data variability from all dimensions, except along one line, while arrows describe the directionality of temporal changes that occur along the line. To validate the patterns detected by non-reductionist operations, reductionist procedures are needed. Integrated (non-reductionist and reductionist) methods can (i) distinguish data subsets that differ immunologically and statistically; (ii) differentiate false-negative from -positive errors; (iii) discriminate disease stages; (iv) capture in vivo, multilevel interactions that consider the patient, the microbe, and antibiotic-mediated responses; and (v) assess dynamics. Integrated methods provide repeatable and biologically interpretable information.

Delineating functional principles of the bow tie structure of a kinase-phosphatase network in the budding yeast

Background

Kinases and phosphatases (KP) form complex self-regulating networks essential for cellular signal processing. In spite of having a wealth of data about interactions among KPs and their substrates, we have very limited models of the structures of the directed networks they form and consequently our ability to formulate hypotheses about how their structure determines the flow of information in these networks is restricted.

Results

We assembled and studied the largest bona fide kinase-phosphatase network (KP-Net) known to date for the yeast Saccharomyces cerevisiae. Application of the vertex sort (VS) algorithm on the KP-Net allowed us to elucidate its hierarchical structure in which nodes are sorted into top, core and bottom layers, forming a bow tie structure with a strongly connected core layer. Surprisingly, phosphatases tend to sort into the top layer, implying they are less regulated by phosphorylation than kinases. Superposition of the widest range of KP biological properties over the KP-Net hierarchy shows that core layer KPs: (i), receive the largest number of inputs; (ii), form bottlenecks implicated in multiple pathways and in decision-making; (iii), and are among the most regulated KPs both temporally and spatially. Moreover, top layer KPs are more abundant and less noisy than those in the bottom layer. Finally, we showed that the VS algorithm depends on node degrees without biasing the biological results of the sorted network. The VS algorithm is available as an R package (https://cran.r-project.org/web/packages/VertexSort/index.html).

Conclusions

The KP-Net model we propose possesses a bow tie hierarchical structure in which the top layer appears to ensure highest fidelity and the core layer appears to mediate signal integration and cell state-dependent signal interpretation. Our model of the yeast KP-Net provides both functional insight into its organization as we understand today and a framework for future investigation of information processing in yeast and eukaryotes in general.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-017-0418-0) contains supplementary material, which is available to authorized users.

MicroRNA degeneracy and pluripotentiality within a Lavallière-tie architecture confers robustness to gene expression networks

Modularity, feedback control, functional redundancy and bowtie architecture have been proposed as key factors that confer robustness to complex biological systems. MicroRNAs (miRNAs) are highly conserved but functionally dispensable. These antinomic properties suggest that miRNAs fine-tune gene expression rather than act as genetic switches. We synthesize published and unpublished data and hypothesize that miRNA pluripotentiality acts to buffer gene expression, while miRNA degeneracy tunes the expression of targets, thus providing robustness to gene expression networks. Furthermore, we propose a Lavallière-tie architecture by integrating signal transduction, miRNAs and protein expression data to model complex gene expression networks.

Signal transduction controls heterogeneous NF-κB dynamics and target gene expression through cytokine-specific refractory states

Cells respond dynamically to pulsatile cytokine stimulation. Here we report that single, or well-spaced pulses of TNFα (>100 min apart) give a high probability of NF-κB activation. However, fewer cells respond to shorter pulse intervals (<100 min) suggesting a heterogeneous refractory state. This refractory state is established in the signal transduction network downstream of TNFR and upstream of IKK, and depends on the level of the NF-κB system negative feedback protein A20. If a second pulse within the refractory phase is IL-1β instead of TNFα, all of the cells respond. This suggests a mechanism by which two cytokines can synergistically activate an inflammatory response. Gene expression analyses show strong correlation between the cellular dynamic response and NF-κB-dependent target gene activation. These data suggest that refractory states in the NF-κB system constitute an inherent design motif of the inflammatory response and we suggest that this may avoid harmful homogenous cellular activation.

The Unspecific Side of Acquired Immunity Against Infectious Disease: Causes and Consequences

Acquired immunity against infectious disease (AIID) has long been considered as strictly dependent on the B and T lymphocytes of the adaptive immune system. Consequently, AIID has been viewed as highly specific to the antigens expressed by pathogens. However, a growing body of data motivates revision of this central paradigm of immunology. Unrelated past infection, vaccination, and chronic infection have been found to induce cross-protection against numerous pathogens. These observations can be partially explained by the poly-specificity of antigenic T and B receptors, the Mackaness effect and trained immunity. In addition, numerous studies highlight the importance of microbiota composition on resistance to infectious disease via direct competition or modulation of the immune response. All of these data support the idea that a non-negligible part of AIID in nature can be nonspecific to the pathogens encountered and even of the antigens expressed by pathogens. As this protection may be dependent on the private T and B repertoires produced by the random rearrangement of genes, past immune history, chronic infection, and microbiota composition, it is largely unpredictable at the individual level. However, we can reasonably expect that a better understanding of the underlying mechanisms will allow us to statistically predict cross-protection at the population level. From an evolutionary perspective, selection of immune mechanisms allowing for partially nonspecific AIID would appear to be advantageous against highly polymorphic and rapidly evolving pathogens. This new emerging paradigm may have several important consequences on our understanding of individual infectious disease susceptibility and our conception of tolerance, vaccination and therapeutic strategies against infection and cancer. It also underscores the importance of viewing the microbiota and persisting infectious agents as integral parts of the immune system.

Reconfiguration of the immune system network during food limitation in the caterpillar Manduca sexta

Dwindling resources might be expected to induce a gradual decline in immune function. However, food limitation has complex and seemingly paradoxical effects on the immune system. Examining these changes from an immune system network perspective may help illuminate the purpose of these fluctuations. We found that food limitation lowered long-term (i.e. lipid) and short-term (i.e. sugars) energy stores in the caterpillar Manduca sexta. Food limitation also: altered immune gene expression, changed the activity of key immune enzymes, depressed the concentration of a major antioxidant (glutathione), reduced resistance to oxidative stress, reduced resistance to bacteria (Gram-positive and -negative bacteria) but appeared to have less effect on resistance to a fungus. These results provide evidence that food limitation led to a restructuring of the immune system network. In severely food-limited caterpillars, some immune functions were enhanced. As resources dwindled within the caterpillar, the immune response shifted its emphasis away from inducible immune defenses (i.e. those responses that are activated during an immune challenge) and increased emphasis on constitutive defenses (i.e. immune components that are produced consistently). We also found changes suggesting that the activation threshold for some immune responses (e.g. phenoloxidase) was lowered. Changes in the configuration of the immune system network will lead to different immunological strengths and vulnerabilities for the organism.

Evolution of bow-tie architectures in biology

Bow-tie or hourglass structure is a common architectural feature found in many biological systems. A bow-tie in a multi-layered structure occurs when intermediate layers have much fewer components than the input and output layers. Examples include metabolism where a handful of building blocks mediate between multiple input nutrients and multiple output biomass components, and signaling networks where information from numerous receptor types passes through a small set of signaling pathways to regulate multiple output genes. Little is known, however, about how bow-tie architectures evolve. Here, we address the evolution of bow-tie architectures using simulations of multi-layered systems evolving to fulfill a given input-output goal. We find that bow-ties spontaneously evolve when the information in the evolutionary goal can be compressed. Mathematically speaking, bow-ties evolve when the rank of the input-output matrix describing the evolutionary goal is deficient. The maximal compression possible (the rank of the goal) determines the size of the narrowest part of the network—that is the bow-tie. A further requirement is that a process is active to reduce the number of links in the network, such as product-rule mutations, otherwise a non-bow-tie solution is found in the evolutionary simulations. This offers a mechanism to understand a common architectural principle of biological systems, and a way to quantitate the effective rank of the goals under which they evolved.

Many biological systems show bow-tie (also called hourglass) architecture. A bow-tie means that a large number of inputs are converted to a small number of intermediates, which then fan out to generate a large number of outputs. For example, cells use a wide variety of nutrients; process them into 12 metabolic precursors, which are then used to make all of the cells biomass. Similar principles exist in biological signaling and in the information processing in the visual system. Despite the ubiquity of bow-tie structures in biology, there is no explanation of how they evolved. Here, we find that bow-ties spontaneously evolve when the information in the evolutionary goal they evolved to satisfy can be compressed. Mathematically, this means that the matrix representing the goal has deficient rank. The maximal compression possible determines the width of the bow-tie—the narrowest part in the network (equal to the rank of the goal matrix). This offers a mechanism to understand a common architectural principle of biological systems, and a way to quantitate the rank of the goals under which they evolved.

Hidden in plain view: degeneracy in complex systems

Degeneracy is a word with two meanings. The popular usage of the word denotes deviance and decay. In scientific discourse, degeneracy refers to the idea that different pathways can lead to the same output. In the biological sciences, the concept of degeneracy has been ignored for a few key reasons. Firstly, the word "degenerate" in popular culture has negative, emotionally powerful associations that do not inspire scientists to consider its technical meaning. Secondly, the tendency of searching for single causes of natural and social phenomena means that scientists can overlook the multi-stranded relationships between cause and effect. Thirdly, degeneracy and redundancy are often confused with each other. Degeneracy refers to dissimilar structures that are functionally similar while redundancy refers to identical structures. Degeneracy can give rise to novelty in ways that redundancy cannot. From genetic codes to immunology, vaccinology and brain development, degeneracy is a crucial part of how complex systems maintain their functional integrity. This review article discusses how the scientific concept of degeneracy was imported into genetics from physics and was later introduced to immunology and neuroscience. Using examples of degeneracy in immunology, neuroscience and linguistics, we demonstrate that degeneracy is a useful way of understanding how complex systems function. Reviewing the history and theoretical scope of degeneracy allows its usefulness to be better appreciated, its coherency to be further developed, and its application to be more quickly realized.

An explanatory evo-devo model for the developmental hourglass

The "developmental hourglass'' describes a pattern of increasing morphological divergence towards earlier and later embryonic development, separated by a period of significant conservation across distant species (the "phylotypic stage''). Recent studies have found evidence in support of the hourglass effect at the genomic level. For instance, the phylotypic stage expresses the oldest and most conserved transcriptomes. However, the regulatory mechanism that causes the hourglass pattern remains an open question. Here, we use an evolutionary model of regulatory gene interactions during development to identify the conditions under which the hourglass effect can emerge in a general setting. The model focuses on the hierarchical gene regulatory network that controls the developmental process, and on the evolution of a population under random perturbations in the structure of that network. The model predicts, under fairly general assumptions, the emergence of an hourglass pattern in the structure of a temporal representation of the underlying gene regulatory network. The evolutionary age of the corresponding genes also follows an hourglass pattern, with the oldest genes concentrated at the hourglass waist. The key behind the hourglass effect is that developmental regulators should have an increasingly specific function as development progresses. Analysis of developmental gene expression profiles from Drosophila melanogaster and Arabidopsis thaliana provide consistent results with our theoretical predictions.

Melatonin regulates mesenchymal stem cell differentiation: a review

Among the numerous functions of melatonin, the control of survival and differentiation of mesenchymal stem cells (MSCs) has been recently proposed. MSCs are a heterogeneous population of multipotent elements resident in tissues such as bone marrow, muscle, and adipose tissue, which are primarily involved in developmental and regeneration processes, gaining thus increasing interest for tissue repair and restoration therapeutic protocols. Receptor-dependent and receptor-independent responses to melatonin are suggested to occur in these cells. These involve antioxidant or redox-dependent functions of this indolamine as well as secondary effects resulting from autocrine and paracrine responses. Inflammatory cytokines and adipokines, proangiogenic/mitogenic stimuli, and other mediators that influence the differentiation processes may affect the survival and functional integrity of these mesenchymal precursor cells. In this scenario, melatonin seems to regulate signaling pathways that drive commitment and differentiation of MSC into osteogenic, chondrogenic, adipogenic, or myogenic lineages. Common pathways suggested to be involved as master regulators of these processes are the Wnt/β-catenin pathway, the MAPKs and the, TGF-β signaling. In this respect melatonin emerges a novel and potential modulator of MSC lineage commitment and adipogenic differentiation. These and other aspects of the physiological and pharmacological effects of melatonin as regulator of MSC are discussed in this review.

Towards a liquid self: how time, geography, and life experiences reshape the biological identity

The conceptualization of immunological self is amongst the most important theories of modern biology, representing a sort of theoretical guideline for experimental immunologists, in order to understand how host constituents are ignored by the immune system (IS). A consistent advancement in this field has been represented by the danger/damage theory and its subsequent refinements, which at present represents the most comprehensive conceptualization of immunological self. Here, we present the new hypothesis of "liquid self," which integrates and extends the danger/damage theory. The main novelty of the liquid self hypothesis lies in the full integration of the immune response mechanisms into the host body's ecosystems, i.e., in adding the temporal, as well as the geographical/evolutionary and environmental, dimensions, which we suggested to call "immunological biography." Our hypothesis takes into account the important biological changes occurring with time (age) in the IS (including immunosenescence and inflammaging), as well as changes in the organismal context related to nutrition, lifestyle, and geography (populations). We argue that such temporal and geographical dimensions impinge upon, and continuously reshape, the antigenicity of physical entities (molecules, cells, bacteria, viruses), making them switching between "self" and "non-self" states in a dynamical, "liquid" fashion. Particular attention is devoted to oral tolerance and gut microbiota, as well as to a new potential source of unexpected self epitopes produced by proteasome splicing. Finally, our framework allows the set up of a variety of testable predictions, the most straightforward suggesting that the immune responses to defined molecules representing potentials antigens will be quantitatively and qualitatively quite different according to the immuno-biographical background of the host.

Oxytocin's role in anxiety: a critical appraisal

A growing literature suggests that the oxytocin (OT) system may play a role in human anxiety states, anxiety-related traits, and moreover, that this system may be a target for the development of novel anxiolytic treatments. However, studies of OT's acute and chronic effects on various aspects of anxiety have produced mixed results. In this forward-looking review, we discuss the myriad phenomena to which the term "anxiety" is applied in the OT literature and the problem this presents developing a coherent picture of OT's role in anxiety. We then survey several different fields of research that support the role of the OT system in human anxiety, including evolutionary perspectives, translational and neuroimaging research, genetic studies, and clinical trials of intranasal OT. As an outgrowth of this data, we propose a "bowtie" model of OT's role at the interface of social attachment and anxiety. We next direct attention to understudied brain regions and neural circuits which may be important to study in OT experiments in humans anxiety disorders. Finally, we conclude by proposing questions and priorities for studying both the clinical potential of OT in anxiety, as well as mechanisms that may underlie this potential. Crucially, these priorities include targeted proof-of-concept clinical trials of IN OT in certain anxiety disorders, including investigations of individual moderators of OT's anxiolytic effects (i.e. sex, genetic factors, and early experience). This article is part of a Special Issue entitled Oxytocin and Social Behav.

Epigenomics and the concept of degeneracy in biological systems

Researchers in the field of epigenomics are developing more nuanced understandings of biological complexity, and exploring the multiple pathways that lead to phenotypic expression. The concept of degeneracy-referring to the multiple pathways that a system recruits to achieve functional plasticity-is an important conceptual accompaniment to the growing body of knowledge in epigenomics. Distinct from degradation, redundancy and dilapidation; degeneracy refers to the plasticity of traits whose function overlaps in some environments, but diverges in others. While a redundant system is composed of repeated identical elements performing the same function, a degenerate system is composed of different elements performing similar or overlapping functions. Here, we describe the degenerate structure of gene regulatory systems from the basic genetic code to flexible epigenomic modifications, and discuss how these structural features have contributed to organism complexity, robustness, plasticity and evolvability.

Ecological immunology in a fluctuating environment: an integrative analysis of tree swallow nestling immune defense

Evolutionary ecologists have long been interested by the link between different immune defenses and fitness. Given the importance of a proper immune defense for survival, it is important to understand how its numerous components are affected by environmental heterogeneity. Previous studies targeting this question have rarely considered more than two immune markers. In this study, we measured seven immune markers (response to phytohemagglutinin (PHA), hemolysis capacity, hemagglutination capacity, plasma bactericidal capacity, percentage of lymphocytes, percentage of heterophils, and percentage of eosinophils) in tree swallow (Tachycineta bicolor) nestlings raised in two types of agro-ecosystems of contrasted quality and over 2 years. First, we assessed the effect of environmental heterogeneity (spatial and temporal) on the strength and direction of correlations between immune measures. Second, we investigated the effect of an immune score integrating information from several immune markers on individual performance (including growth, mass at fledging and parasite burden). Both a multivariate and a pair-wise approach showed variation in relationships between immune measures across years and habitats. We also found a weak association between the integrated score of nestling immune function and individual performance, but only under certain environmental conditions. We conclude that the ecological context can strongly affect the interpretation of immune defenses in the wild. Given that spatiotemporal variations are likely to affect individual immune defenses, great caution should be used when generalizing conclusions to other study systems.

Non-local competition drives both rapid divergence and prolonged stasis in a model of speciation in populations with degenerate resource consumption

The theory of speciation is dominated by adaptationist thinking, with less attention to mechanisms that do not affect species adaptation. Degeneracy – the imperfect specificity of interactions between diverse elements of biological systems and their environments – is key to the adaptability of populations. A mathematical model was explored in which population and resource were distributed one-dimensionally according to trait value. Resource consumption was degenerate – neither strictly location-specific nor location-independent. As a result, the competition for resources among the elements of the population was non-local. Two modeling approaches, a modified differential-integral Verhulstian equation and a cellular automata model, showed similar results: narrower degeneracy led to divergent dynamics with suppression of intermediate forms, whereas broader degeneracy led to suppression of diversifying forms, resulting in population stasis with increasing phenotypic homogeneity. Such behaviors did not increase overall adaptation because they continued after the model populations achieved maximal resource consumption rates, suggesting that degeneracy-driven distributed competition for resources rather than selective pressure toward more efficient resource exploitation was the driving force. The solutions were stable in the presence of limited environmental stochastic variability or heritable phenotypic variability. A conclusion was made that both dynamic diversification and static homogeneity of populations may be outcomes of the same process – distributed competition for resource not affecting the overall adaptation – with the difference between them defined by the spread of trait degeneracy in a given environment. Thus, biological degeneracy is a driving force of both speciation and stasis in biology, which, by themselves, are not necessarily adaptive in nature.

Differential network entropy reveals cancer system hallmarks

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network we here demonstrate that cancer cells are characterised by an increase in network entropy. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local network entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local correlation patterns. In particular, we find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in network entropy. These findings may have potential implications for identifying novel drug targets.

Degeneracy allows for both apparent homogeneity and diversification in populations

Trait diversity - the substrate for natural selection - is necessary for adaptation through selection, particularly in populations faced with environmental changes that diminish population fitness. In habitats that remain unchanged for many generations, stabilizing selection maximizes exploitation of resources by reducing trait diversity to a narrow optimal range. One might expect that such ostensibly homogeneous populations would have a reduced potential for heritable adaptive responses when faced with fitness-reducing environmental changes. However, field studies have documented populations that, even after long periods of evolutionary stasis, can still rapidly evolve in response to changed environmental conditions. We argue that degeneracy, the ability of diverse population elements to function similarly, can satisfy both the current need to maximize fitness and the future need for diversity. Degenerate ensembles appear functionally redundant in certain environmental contexts and functionally diverse in others. We propose that genetic variation not contributing to the observed range of phenotypes in a current population, also known as cryptic genetic variation (CGV), is a specific case of degeneracy. We argue that CGV, which gradually accumulates in static populations in stable environments, reveals hidden trait differences when environments change. By allowing CGV accumulation, static populations prepare themselves for future rapid adaptations to environmental novelty. A greater appreciation of degeneracy's role in resolving the inherent tension between current stabilizing selection and future directional selection has implications in conservation biology and may be applied in social and technological systems to maximize current performance while strengthening the potential for future changes.

Biological robustness: paradigms, mechanisms, and systems principles

Robustness has been studied through the analysis of data sets, simulations, and a variety of experimental techniques that each have their own limitations but together confirm the ubiquity of biological robustness. Recent trends suggest that different types of perturbation (e.g., mutational, environmental) are commonly stabilized by similar mechanisms, and system sensitivities often display a long-tailed distribution with relatively few perturbations representing the majority of sensitivities. Conceptual paradigms from network theory, control theory, complexity science, and natural selection have been used to understand robustness, however each paradigm has a limited scope of applicability and there has been little discussion of the conditions that determine this scope or the relationships between paradigms. Systems properties such as modularity, bow-tie architectures, degeneracy, and other topological features are often positively associated with robust traits, however common underlying mechanisms are rarely mentioned. For instance, many system properties support robustness through functional redundancy or through response diversity with responses regulated by competitive exclusion and cooperative facilitation. Moreover, few studies compare and contrast alternative strategies for achieving robustness such as homeostasis, adaptive plasticity, environment shaping, and environment tracking. These strategies share similarities in their utilization of adaptive and self-organization processes that are not well appreciated yet might be suggestive of reusable building blocks for generating robust behavior.

Data driven linear algebraic methods for analysis of molecular pathways: application to disease progression in shock/trauma

MOTIVATION

Although trauma is the leading cause of death for those below 45years of age, there is a dearth of information about the temporal behavior of the underlying biological mechanisms in those who survive the initial trauma only to later suffer from syndromes such as multiple organ failure. Levels of serum cytokines potentially affect the clinical outcomes of trauma; understanding how cytokine levels modulate intra-cellular signaling pathways can yield insights into molecular mechanisms of disease progression and help to identify targeted therapies. However, developing such analyses is challenging since it necessitates the integration and interpretation of large amounts of heterogeneous, quantitative and qualitative data. Here we present the Pathway Semantics Algorithm (PSA), an algebraic process of node and edge analyses of evoked biological pathways over time for in silico discovery of biomedical hypotheses, using data from a prospective controlled clinical study of the role of cytokines in multiple organ failure (MOF) at a major US trauma center. A matrix algebra approach was used in both the PSA node and PSA edge analyses with different matrix configurations and computations based on the biomedical questions to be examined. In the edge analysis, a percentage measure of crosstalk called XTALK was also developed to assess cross-pathway interference.

RESULTS

In the node/molecular analysis of the first 24h from trauma, PSA uncovered seven molecules evoked computationally that differentiated outcomes of MOF or non-MOF (NMOF), of which three molecules had not been previously associated with any shock/trauma syndrome. In the edge/molecular interaction analysis, PSA examined four categories of functional molecular interaction relationships--activation, expression, inhibition, and transcription--and found that the interaction patterns and crosstalk changed over time and outcome. The PSA edge analysis suggests that a diagnosis, prognosis or therapy based on molecular interaction mechanisms may be most effective within a certain time period and for a specific functional relationship.

Charting the NF-κB pathway interactome map

Inflammation is part of a complex physiological response to harmful stimuli and pathogenic stress. The five components of the Nuclear Factor κB (NF-κB) family are prominent mediators of inflammation, acting as key transcriptional regulators of hundreds of genes. Several signaling pathways activated by diverse stimuli converge on NF-κB activation, resulting in a regulatory system characterized by high complexity. It is increasingly recognized that the number of components that impinges upon phenotypic outcomes of signal transduction pathways may be higher than those taken into consideration from canonical pathway representations. Scope of the present analysis is to provide a wider, systemic picture of the NF-κB signaling system. Data from different sources such as literature, functional enrichment web resources, protein-protein interaction and pathway databases have been gathered, curated, integrated and analyzed in order to reconstruct a single, comprehensive picture of the proteins that interact with, and participate to the NF-κB activation system. Such a reconstruction shows that the NF-κB interactome is substantially different in quantity and quality of components with respect to canonical representations. The analysis highlights that several neglected but topologically central proteins may play a role in the activation of NF-κB mediated responses. Moreover the interactome structure fits with the characteristics of a bow tie architecture. This interactome is intended as an open network resource available for further development, refinement and analysis.

Evolution of immune-neuroendocrine integration from an ecological immunology perspective

Bow tie architecture can support evolutionary integration between the immune and neuroendocrine systems, answering ecological immunology demands in terms of economy and efficiency.