Minimal Network Research Articles

Asynchronous Chaos and Bifurcations in a Model of Two Coupled Identical Hindmarsh – Rose Neurons

We study a minimal network of two coupled neurons described by the Hindmarsh – Rose model with a linear coupling. We suppose that individual neurons are identical and study whether the dynamical regimes of a single neuron would be stable synchronous regimes in the model of two coupled neurons. We find that among synchronous regimes only regular periodic spiking and quiescence are stable in a certain range of parameters, while no bursting synchronous regimes are stable. Moreover, we show that there are no stable synchronous chaotic regimes in the parameter range considered. On the other hand, we find a wide range of parameters in which a stable asynchronous chaotic regime exists. Furthermore, we identify narrow regions of bistability, when synchronous and asynchronous regimes coexist. However, the asynchronous attractor is monostable in a wide range of parameters. We demonstrate that the onset of the asynchronous chaotic attractor occurs according to the Afraimovich – Shilnikov scenario. We have observed various asynchronous firing patterns: irregular quasi-periodic and chaotic spiking, both regular and chaotic bursting regimes, in which the number of spikes per burst varied greatly depending on the control parameter.

The Metabolic Building Blocks of a Minimal Cell

Simple SummaryManufacturing artificial living cells would open endless research possibilities in basic and applied sciences. With this motivation, many research groups are developing methodologies to construct a stable minimal cell that is capable of achieving metabolic homeostasis, reproducing, and evolving in a controlled environment. Using as a template the gene set for a minimal cell proposed previously by Gil and coworkers, we have put together a network depicting its inferred minimal metabolism needed for life. This network has been further compressed as a metabolic Directed Acyclic Graph (m-DAG) in order to better visualize its topology and to find its essential reactions (i.e., critical reactions to maintain the network’s connectivity). We have also compared this minimal m-DAG to those of the smallest natural genome known until now and a synthetic minimal cell created in the laboratory. The modeling of m-DAGs based on minimal metabolisms can be a first approach for the synthesis and manipulation of minimal cells.Defining the essential gene components for a system to be considered alive is a crucial step toward the synthesis of artificial life. Fifteen years ago, Gil and coworkers proposed the core of a putative minimal bacterial genome, which would provide the capability to achieve metabolic homeostasis, reproduce, and evolve to a bacterium in an ideally controlled environment. They also proposed a simplified metabolic chart capable of providing energy and basic components for a minimal living cell. For this work, we have identified the components of the minimal metabolic network based on the aforementioned studies, associated them to the KEGG database and, by applying the MetaDAG methodology, determined its Metabolic Building Blocks (MBB) and reconstructed its metabolic Directed Acyclic Graph (m-DAG). The reaction graph of this metabolic network consists of 80 compounds and 98 reactions, while its m-DAG has 36 MBBs. Additionally, we identified 12 essential reactions in the m-DAG that are critical for maintaining the connectivity of this network. In a similar manner, we reconstructed the m-DAG of JCVI-syn3.0, which is an artificially designed and manufactured viable cell whose genome arose by minimizing the one from Mycoplasma mycoides JCVI-syn1.0, and of “Candidatus Nasuia deltocephalinicola”, the bacteria with the smallest natural genome known to date. The comparison of the m-DAGs derived from a theoretical, an artificial, and a natural genome denote slightly different lifestyles, with a consistent core metabolism. The MetaDAG methodology we employ uses homogeneous descriptors and identifiers from the KEGG database, so that comparisons between bacterial strains are not only easy but also suitable for many research fields. The modeling of m-DAGs based on minimal metabolisms can be the first step for the synthesis and manipulation of minimal cells.

The internal structure of the state protection of children in Mendoza: the actors and their movements (1995-1999)

The state protection of children in the last 30 years has a critical reflection of the ratification of the first human rights treaty for children and adolescents. Multiple glances focused on the bureaucratic normative apparatuses that operated/operate on children's bodies, to glimpse the configuration of institutional practices. This article attempts to reconstruct the circuits generated through the articulation and power networks related to the state protection of institutionalized childhood (1995 - 1999), through the study of the actors involved in the institutionalization in the province of Mendoza. The methodology used is hermeneutical, heuristic and will be carried out from the analysis of the case of the “witnesses”. For this, three cases of institutionalized boys, girls, and adolescents have been chosen, reflected in institutional files. The results raise the relevance of four institutional actors that are key in institutional actions, whose profiles could be translated into the decision-maker, the communicational control, the sentinel, and the public force. On the other hand, in the minimal networks of the cases presented, the subordination of one (executive) power over another state (judicial) power is proposed. Finally, differentiated power dynamics are indicated between the center and the peripheries of the province of Mendoza, Argentina.

Minimal Series–Parallel Network Realizations of Bicubic Impedances

An important open problem in the synthesis of passive controllers is to obtain a passive network that realizes an arbitrary given impedance function and contains the least possible number of elements. This problem has its origins in electric circuit theory, and is directly applicable to the cost-effective design of mechanical systems containing the inerter. Despite a rich history, the problem can only be considered solved for networks that contain at most two energy storage elements, and in a small number of other special cases. In this article, we solve the minimal network realization problem for the class of impedances realized by series–parallel networks containing at most three energy storage elements. To accomplish this, we develop a novel continuity-based approach to eliminate redundant elements from a network.

Reconfigurable Web-Interface Remote Lab for Instrumentation and Electronic Learning

Lab sessions in engineering education are designed to reinforce theoretical concepts. However, usually there are not enough time to reinforce all of them. Remote and virtual lab give students more time for reinforce those concepts. In particular, with remote labs, this can be done interacting with real lab equipment and specific configurations. This work proposes a flexible configuration for Remote Lab Sessions, based on some of 2019 most popular programming languages (Python and JavaScript). This configuration needed minimal network privileges, it is easily to scale and reconfigure. Its structure is based on a unique Reception-Server (which hosts User database, and Time Shift Manager, it is accessible from The Internet, and connect Users with Instruments-Servers) and some Instrument-Servers (which manage hardware connection and host experiences). Users always connect to Reception-Server, and book a shift for an experience. During the time range associate to that shift, User is internally forwarded to Instrument-Server associated with selected experience, so User is still connected to Reception-Serer. In this way, Reception-Server acts as a firewall, protecting Instrument-Servers, which never are open to The Internet. A triple evaluation system is implemented, User session logging and auto-evaluation (objectives accomplished) a knowledge test and an interaction survey. An experience is implemented, controlling a DC source using Standard Commands for Programmable Instruments.

Network-Coding Solutions for Minimal Combination Networks and Their Sub-Networks

Minimal multicast networks are fascinating and efficient combinatorial objects, where the removal of a single link makes it impossible for all receivers to obtain all messages. We study the structure of such networks, and prove some constraints on their possible solutions. We then focus on the combination network, which is one of the simplest and most insightful network in network-coding theory. Of particular interest are minimal combination networks. We study the gap in alphabet size between vector-linear and scalar-linear network-coding solutions for such minimal combination networks and some of their sub-networks. For minimal multicast networks with two source messages we find the maximum possible gap. We define and study sub-networks of the combination network, which we call Kneser networks, and prove that they attain the upper bound on the gap with equality. We also prove that the study of this gap may be limited to the study of sub-networks of minimal combination networks, by using graph homomorphisms connected with the $q$-analog of Kneser graphs. Additionally, we prove a gap for minimal multicast networks with three or more source messages by studying Kneser networks. Finally, an upper bound on the gap for full minimal combination networks shows nearly no gap, or none in some cases. This is obtained using an MDS-like bound for subspaces over a finite field.

Local Immunodeficiency: Role of Neutral Viruses.

This paper analyzes the role of neutral viruses in the phenomenon of local immunodeficiency. We show that, even in the absence of altruistic viruses, neutral viruses can support the existence of persistent viruses and thus local immunodeficiency. However, in all such cases neutral viruses can maintain only bounded (relatively small) concentration of persistent viruses. Moreover, in all such cases the state of local immunodeficiency could only be marginally stable, while it is known that altruistic viruses can maintain stable local immunodeficiency. We also present an absolutely minimal cross-immunoreactivity network where a stable and robust state of local immunodeficiency can be maintained. It is now a challenge to synthetic biology to build such small networks with stable local immunodeficiency. Another important challenge for biology is to understand which types of viruses can play a role of persistent, altruistic and neutral ones and whether a role which a given virus plays depends on the structure (topology) of a given cross-immunoreactivity network.

The landscape and flux of a minimum network motif, Wu Xing* *Project supported by the National Natural Science Foundation of China (Grant No. 21721003) and the Fund from the Ministry of Science and Technology of China (Grant No. 2016YFA0203200).

Wu-Xing theory is an ancient philosophy that serves as a guiding principle in the traditional Chinese medicine (TCM). It has been used to explain the unbalance among the TCM organ systems in disease states and provide treatment philosophy qualitatively. Until now, it is still a challenge to explore the Wu-Xing theory beyond its philosophical nature. In this study, we established a quantitative framework using the landscape and flux theory to characterize the nature of the Wu-Xing theory from a perspective of a minimal network motif and leave certain specific functional aspects of Wu-Xing theory for future exploration. We uncovered the irregular ring shape of projection landscape for the Wu-Xing network with several local basins and barriers. We found that the dynamics of the self-organized Wu-Xing system was determined by the underlying negative landscape gradient force and the nonequilibrium rotational flux. While the shape of the Wu-Xing landscape determines the stabilities of the states, the rotational flux guarantees the persistent periodic oscillation and the stability of the flow. This provides a physical and quantitative basis for Yin–Yang duality of the driving forces for determining the dynamics and behaviors of the living systems. Applying landscape and flux analysis, we can identify the key parameter for the dynamics/function of Wu-Xing network. These findings allow us to have a deeper understanding of the scientific merits of the ancient Wu-Xing theory from the network motif perspective.

A generalizable formalism for computing uncertainties in UTC

Algorithms to compute the statistical and systematic uncertainties in the difference between Coordinated Universal Time (UTC) and individual laboratory UTC realizations were published in several different, but equivalent, forms the early twenty-first century, at a time when the UTC algorithm was based on a minimal network. In this paper we extend the theory to compute the uncertainties in a manner entirely consistent with the earlier work, but which enables application to UTC computations employing redundant links, and correlated calibrations.

Optimal Placement of Distributed Generation in Transmission Network for Loss Minimization via Multistage Artificial Immune System

Optimal Placement of Distributed Generation in Transmission Network for Loss Minimization via Multistage Artificial Immune System

Classifying Community Organizational Health Communication Networks: Local Health Department Recognition of Public Information-Sharing Partners Across Sectors.

Local health departments (LHDs) operate within complex, multisectoral organizational communication networks. Network composition may affect priorities, processes, and the reach of health information to key stakeholders. This study seeks to elucidate variation in local network structures to examine how different constellations may affect information sharing across audiences. This study analyzes data from a 2016 US survey of 491 metropolitan LHDs and 556 nonmetropolitan LHDs. Researchers first conducted social network analysis of network density, defined as the total number of potential organizations contributing to a jurisdiction's health communication activities. Researchers then conducted logistic regression to compare the relationship between network density and reported health communication activities targeting 3 specific audiences: policy makers, lay publics, and mass media. Three network types emerged on the basis of the number of organizations that contribute to health communication activities, with low-density Minimal networks more common in nonmetropolitan jurisdictions and higher-density Expanded and Robust networks more common in metropolitan jurisdictions. LHDs in Minimal networks were significantly less likely to communicate with policy makers, lay publics, and mass media than their counterparts in higher-density networks (P < .05). LHDs are embedded in organizational communication networks that vary in both the number of communication partners and the types of audiences reached. Examining their own local organizational communication networks may provide insights into LHDs that wish to improve the effectiveness of public health messaging. By adding organizational communication partners and reaching new audiences, LHDs in Minimal networks can expand the reach of messages designed to help policy makers, communities, and individuals promote health and prevent disease.

CDC-42 Interactions with Par Proteins Are Critical for Proper Patterning in Polarization.

Many cells rearrange proteins and other components into spatially distinct domains in a process called polarization. This asymmetric patterning is required for a number of biological processes including asymmetric division, cell migration, and embryonic development. Proteins involved in polarization are highly conserved and include members of the Par and Rho protein families. Despite the importance of these proteins in polarization, it is not yet known how they interact and regulate each other to produce the protein localization patterns associated with polarization. In this study, we develop and analyse a biologically based mathematical model of polarization that incorporates interactions between Par and Rho proteins that are consistent with experimental observations of CDC-42. Using minimal network and eFAST sensitivity analyses, we demonstrate that CDC-42 is predicted to reinforce maintenance of anterior PAR protein polarity which in turn feedbacks to maintain CDC-42 polarization, as well as supporting posterior PAR protein polarization maintenance. The mechanisms for polarity maintenance identified by these methods are not sufficient for the generation of polarization in the absence of cortical flow. Additional inhibitory interactions mediated by the posterior Par proteins are predicted to play a role in the generation of Par protein polarity. More generally, these results provide new insights into the role of CDC-42 in polarization and the mutual regulation of key polarity determinants, in addition to providing a foundation for further investigations.

DNA Nanotechnology: Engineering Light‐Responsive Contractile Actomyosin Networks with DNA Nanotechnology (Adv. Biosys. 9/2020)

In article number 2000102, Ilia Platzman, Kerstin Göpfrich, Joachim P. Spatz, and co-workers engineer minimal contractile actomyosin networks for synthetic cells. They employ DNA nanotechnology combined with light-triggered actuation to control the contraction dynamics. Symmetry breaking is achieved and quantified in cell-sized compartments, showcasing how an engineering approach to synthetic biology can provide a shortcut toward complex function.

Minimal chimera states in phase-lag coupled mechanical oscillators

We obtain experimental chimera states in the minimal network of three identical mechanical oscillators (metronomes), by introducing phase-lagged all-to-all coupling. For this, we have developed a real-time model-in-the-loop coupling mechanism that allows for flexible and online change of coupling topology, strength and phase-lag. The chimera states manifest themselves as a mismatch of average frequency between two synchronous and one desynchronized oscillator. We find this kind of striking “chimeric” behavior is robust in a wide parameter region. At other parameters, however, chimera state can lose stability and the system behavior manifests itself as a heteroclinic switching between three saddle-type chimeras. Our experimental observations are in a qualitative agreement with the model simulation.

Consideration of Social Disadvantages for Understanding and Preventing Obesity in Children.

Addressing social disadvantages that lead to obesity should be a public health priority. Obesity prevalence among children and adolescents has reached a plateau in countries with high income but it continues rising in low-income and middle-income countries. In high-income countries, an elevated prevalence of obesity is found among racial and ethnic minority groups and individuals from disadvantaged socioeconomic backgrounds. In addition to classic socioeconomic status (SES) factors, like income, parental education, and occupation, recent publications have linked parental social disadvantages, such as minimal social network, non-traditional family structure, migrant status and unemployment, with obesogenic behaviors and obesity among children. Socio-ecological models of obesity in children can explain the influence of classic SES factors, social disadvantages, culture, and genes on behaviors that could lead to obesity, contributing to the elevated prevalence of obesity. Obesity is a multifactorial disease in which multilevel interventions seem to be the most effective approach to prevent obesity in children, but previous meta-analyses have found that multilevel interventions had poor or inconsistent results. Despite these results, some multilevel interventions addressing specific disadvantaged social groups have shown beneficial effects on children's weight and energy balance-related behaviors, while other interventions have benefited children from both disadvantaged and non-disadvantaged backgrounds. Considering obesity as a worldwide problem, the World Health Organization, the European Commission, and the National Institutes of Health recommend the implementation of obesity prevention programs, but the implementation of such programs without taking into consideration social disadvantages may be an unsuccessful approach. Therefore, the present publication consists of a review of the pertinent literature related to social disadvantage and its consequences for behaviors that could lead to childhood obesity. In addition, we will discuss the relationship between social disadvantages and the socio-ecological model of obesity in children. Finally, we will summarize the relevant aspects of multilevel intervention programs aiming to prevent obesity in children and provide recommendations for future research and intervention approaches to improve weight status in children with social disadvantages.

Predicting Alzheimer's disease progression using deep recurrent neural networks

Early identification of individuals at risk of developing Alzheimer's disease (AD) dementia is important for developing disease-modifying therapies. In this study, given multimodal AD markers and clinical diagnosis of an individual from one or more timepoints, we seek to predict the clinical diagnosis, cognition and ventricular volume of the individual for every month (indefinitely) into the future. We proposed and applied a minimal recurrent neural network (minimalRNN) model to data from The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) challenge, comprising longitudinal data of 1677 participants (Marinescu et al., 2018) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We compared the performance of the minimalRNN model and four baseline algorithms up to 6 years into the future. Most previous work on predicting AD progression ignore the issue of missing data, which is a prevalent issue in longitudinal data. Here, we explored three different strategies to handle missing data. Two of the strategies treated the missing data as a “preprocessing” issue, by imputing the missing data using the previous timepoint (“forward filling”) or linear interpolation (“linear filling). The third strategy utilized the minimalRNN model itself to fill in the missing data both during training and testing (“model filling”). Our analyses suggest that the minimalRNN with “model filling” compared favorably with baseline algorithms, including support vector machine/regression, linear state space (LSS) model, and long short-term memory (LSTM) model. Importantly, although the training procedure utilized longitudinal data, we found that the trained minimalRNN model exhibited similar performance, when using only 1 input timepoint or 4 input timepoints, suggesting that our approach might work well with just cross-sectional data. An earlier version of our approach was ranked 5th (out of 53 entries) in the TADPOLE challenge in 2019. The current approach is ranked 2nd out of 63 entries as of June 3rd, 2020.

Low genetic differentiation between apotheciate Usnea florida and sorediate Usnea subfloridana (Parmeliaceae, Ascomycota) based on microsatellite data

Accurate species delimitation has a pivotal role in conservation biology, and it is especially important for threatened species where decisions have political and economic consequences. Finding and applying appropriate character sets and analytical tools to resolve interspecific relationships remains challenging in lichenized fungi. The main aim of our study was to re-assess the species boundaries between Usnea subfloridana and Usnea florida, which have been phylogenetically indistinguishable until now, but are different in reproductive mode and ecological preferences, using fungal-specific simple sequence repeats (SSR), i.e. microsatellite markers. Bayesian clustering analysis, discriminant analysis of principal components (DAPC), minimal spanning network (MSN), and principal component analysis (PCA) failed to separate U. florida and U. subfloridana populations. However, a low significant differentiation between the two taxa was observed across all populations according to AMOVA results. Also, analysis of shared haplotypes and statistical difference in clonal diversity (M) supported the present-day isolation between the apotheciate U. florida and predominantly sorediate U. subfloridana. Our results do not provide a clear support either for the separation of species in this pair or the synonymization of U. florida and U. subfloridana. We suggest that genome-wide data could help resolve the taxonomic question in this species pair.

Functional definition of a transcription factor hierarchy regulating T cell lineage commitment.

T cell factor 1 (Tcf1) is the first T cell-specific protein induced by Notch signaling in the thymus, leading to the activation of two major target genes, Gata3 and Bcl11b. Tcf1 deficiency results in partial arrests in T cell development, high apoptosis, and increased development of B and myeloid cells. Phenotypically, seemingly fully T cell-committed thymocytes with Tcf1 deficiency have promiscuous gene expression and an altered epigenetic profile and can dedifferentiate into more immature thymocytes and non-T cells. Restoring Bcl11b expression in Tcf1-deficient cells rescues T cell development but does not strongly suppress the development of non-T cells; in contrast, expressing Gata3 suppresses their development but does not rescue T cell development. Thus, T cell development is controlled by a minimal transcription factor network involving Notch signaling, Tcf1, and the subsequent division of labor between Bcl11b and Gata3, thereby ensuring a properly regulated T cell gene expression program.

Engineering Light‐Responsive Contractile Actomyosin Networks with DNA Nanotechnology

External control and precise manipulation is key for the bottom-up engineering of complex synthetic cells. Minimal actomyosin networks have been reconstituted into synthetic cells; however, their light-triggered symmetry breaking contraction has not yet been demonstrated. Here, light-activated directional contractility of a minimal synthetic actomyosin network inside microfluidic cell-sized compartments is engineered. Actin filaments, heavy-meromyosin-coated beads, and caged ATP are co-encapsulated into water-in-oil droplets. ATP is released upon illumination, leading to a myosin-generated force which results in a motion of the beads along the filaments and hence a contraction of the network. Symmetry breaking is achieved using DNA nanotechnology to establish a link between the network and the compartment periphery. It is demonstrated that the DNA-linked actin filaments contract to one side of the compartment forming actin asters and quantify the dynamics of this process. This work exemplifies that an engineering approach to bottom-up synthetic biology, combining biological and artificial elements, can circumvent challenges related to active multi-component systems and thereby greatly enrich the complexity of synthetic cellularsystems.

Proposed minimal essential co-expression and physical interaction networks involved in the development of cognition impairment in human mid and late life.

The aim of this study was to identify the minimal essential co-expression and physical interaction networks involved in the development of cognition impairment in human mid and late life. We searched the Online Mendelian Inheritance in Man (OMIM) database to extract the validated human genes annotated (until March 2020) for five major disorders of pathophysiological overlap and sequential chronological occurrence in human, including multiple sclerosis, type 2 diabetes mellitus, Alzheimer's disease, vascular dementia, and Lewy body dementia. Gene co-expression and physical interaction networks were subsequently constructed for the overlapping genes across the selected disorders. Remarkably, each of the gene co-expression and physical interaction networks consisted of single clusters (P = 0.0005 and P = 1 × 10-16, respectively). APP was the major hub in the integrated and tissue-specific co-expression networks, whereas insulin was the major hub in the physical interaction network. Several other hubs were identified across the identified networks, including TNF, VEGFA, GAPDH, and NOTCH1. We propose the minimal co-expression and physical interaction networks and their single clustering in the development of cognition impairment in human mid and late life. This is a pilot study, warranting identification of more risk genes, using additional validated databases in the future.