Hierarchical structure of biological systems: a bioengineering approach

Hierarchical assembly of foldable polymers and applications in organic optoelectronics and antibacterial or antiviral materials

Aggregation of amphiphilic polymers in block-selective solvents produces different nanostructures, which have been studied extensively for wide-ranging applications. Nevertheless, such immiscibility-driven aggregation does not endow them with the desired structural precision, predictability or surface functional group exposure, which significantly impact their functional applications. More recently, biomimetic folded structures of synthetic macromolecules (mostly oligomers) have come to the fore, but such studies have been limited to probe the secondary structures. In this article, we have collated hierarchical structures of foldamers, especially highlighting our recent contribution to the field of chain-folding regulated assembly of segmented polyurethanes (PUs) and their functional applications. A series of such PUs have been discussed, which contain a segmented hydrocarbon backbone and alternately placed pendant solvophilic groups. In either water or highly non-polar solvents (TCE, MCH), depending on the nature of the pendant group, they exhibit folded structures stabilized by intra-chain H-bonding. Hierarchical assembly of such folded chains by inter-chain H-bonding and/or π-stacking leads to the formation of well-defined nanostructures with functional applications ranging from organic optoelectronics to biomaterials. For example, a segmented PU with appended naphthalene-diimide (NDI) chromophores showed a pleated structure in MCH, which helped in organization of the NDI chromophores within π-stacking distance. Such folded polymer chains eventually produced nanotubular structures with excellent electron mobility. They also showed efficient intercalation of the pyrene (Py) donor by NDI-Py charge-transfer interaction and in this case the mixed nanotubular structure exhibited prominent room-temperature ferroelectricity. On the other hand, having cationic functionalities as the pendant groups such chain-folding regulated assembly produced unilamellar polymersomes with excellent antibacterial activity with very low minimum inhibitory concentrations (<10 μg mL-1). Replacing the pendant amine functionality with sulphate groups made these polyurethanes highly potent antiviral materials. In the absence of the alternating connectivity of the solvophobic and solvophilic segments or rigid hydrocarbon backbone, such folding propensity is destroyed, leading to structural collapse. While significant efforts have been made in correlating primary structures of wide-ranging polymers with their functional applications, this article demonstrates the direct correlation between the secondary structures of polymers and their functional properties.

SBML to bond graphs: From conversion to composition

The Systems Biology Markup Language (SBML) is a popular software-independent XML-based format for describing models of biological phenomena. The BioModels Database is the largest online repository of SBML models. Several tools and platforms are available to support the reuse and composition of SBML models. However, these tools do not explicitly assess whether models are physically plausible or thermodynamically consistent. This often leads to ill-posed models that are physically impossible, impeding the development of realistic complex models in biology. Here, we present a framework that can automatically convert SBML models into bond graphs, which imposes energy conservation laws on these models. The new bond graph models are easily mergeable, resulting in physically plausible coupled models. We illustrate this by automatically converting and coupling a model of pyruvate distribution to a model of the pentose phosphate pathway.

Adipogenic progenitors in different organs: Pathophysiological implications

In physiological conditions, the adipose organ resides in well-defined areas, where it acts providing an energy supply and as an endocrine organ involved in the control of whole-body energy metabolism. Adipose tissue adipokines connect the body's nutritional status to the regulation of energy balance. When it surrounds organs, it provides also for mechanical protection. Adipose tissue has a complex and heterogenous cellular composition that includes adipocytes, adipose tissue-derived stromal and stem cells (ASCs) which are mesenchymal stromal cells, and endothelial and immune cells, which signal to each other and to other tissues to maintain homeostasis. In obesity and in other nutrition related diseases, as well as in age-related diseases, biological and functional changes of adipose tissue give rise to several complications. Obesity triggers alterations of ASCs, impairing adipose tissue remodeling and adipose tissue function, which induces low-grade systemic inflammation, progressive insulin resistance and other metabolic disorders. Adipose tissue grows by hyperplasia recruiting new ASCs and by hypertrophy, up to its expandability limit. To overcome this limitation and to store the excess of nutrients, adipose tissue develops ectopically, involving organs such as muscle, bone marrow and the heart. The origin of ectopic adipose organ is not clearly elucidated, and a possible explanation lies in the stimulation of the adipogenic differentiation of mesenchymal precursor cells which normally differentiate toward a lineage specific for the organ in which they reside. The chronic exposition of these newly-formed adipose depots to the pathological environment, will confer to them all the phenotypic characteristics of a dysfunctional adipose tissue, perpetuating the organ alterations. Visceral fat, but also ectopic fat, either in the liver, muscle or heart, can increase the risk of developing insulin resistance, type 2 diabetes, and cardiovascular diseases. Being able to prevent and to target dysfunctional adipose tissue will avoid the progression towards the complications of obesity and other nutrition-related diseases. The aim of this review is to summarize some of the knowledge regarding the presence of adipose tissue in particular tissues (where it is not usually present), describing the composition of its adipogenic precursors, and the interactions responsible for the development of organ pathologies.

Parallel and hierarchical neural mechanisms for adaptive and predictive behavioral control

Our brain can be recognized as a network of largely hierarchically organized neural circuits that operate to control specific functions, but when acting in parallel, enable the performance of complex and simultaneous behaviors. Indeed, many of our daily actions require concurrent information processing in sensorimotor, associative, and limbic circuits that are dynamically and hierarchically modulated by sensory information and previous learning. This organization of information processing in biological organisms has served as a major inspiration for artificial intelligence and has helped to create in silico systems capable of matching or even outperforming humans in several specific tasks, including visual recognition and strategy-based games. However, the development of human-like robots that are able to move as quickly as humans and respond flexibly in various situations remains a major challenge and indicates an area where further use of parallel and hierarchical architectures may hold promise. In this article we review several important neural and behavioral mechanisms organizing hierarchical and predictive processing for the acquisition and realization of flexible behavioral control. Then, inspired by the organizational features of brain circuits, we introduce a multi-timescale parallel and hierarchical learning framework for the realization of versatile and agile movement in humanoid robots.

INFEKTA-An agent-based model for transmission of infectious diseases: The COVID-19 case in Bogotá, Colombia

The transmission dynamics of the coronavirus—COVID-19—have challenged humankind at almost every level. Currently, research groups around the globe are trying to figure out such transmission dynamics under special conditions such as separation policies enforced by governments. Mathematical and computational models, like the compartmental model or the agent-based model, are being used for this purpose. This paper proposes an agent-based model, called INFEKTA, for simulating the transmission of infectious diseases, not only the COVID-19, under social distancing policies. INFEKTA combines the transmission dynamic of a specific disease, (according to parameters found in the literature) with demographic information (population density, age, and genre of individuals) of geopolitical regions of the real town or city under study. Agents (virtual persons) can move, according to its mobility routines and the enforced social distancing policy, on a complex network of accessible places defined over an Euclidean space representing the town or city. The transmission dynamics of the COVID-19 under different social distancing policies in Bogotá city, the capital of Colombia, is simulated using INFEKTA with one million virtual persons. A sensitivity analysis of the impact of social distancing policies indicates that it is possible to establish a ‘medium’ (i.e., close 40% of the places) social distancing policy to achieve a significant reduction in the disease transmission.

Why is Complexity Science valuable for reaching the goals of the UN 2030 Agenda?

The goals and targets included in the 2030 Agenda compiled by the United Nations want to stimulate action in areas of critical importance for humanity and the Earth. These goals and targets regard everyone on Earth from both the health and economic and social perspectives. Reaching these goals means to deal with Complex Systems. Therefore, Complexity Science is undoubtedly valuable. However, it needs to extend its scope and focus on some specific objectives. This article proposes a development of Complexity Science that will bring benefits for achieving the United Nations' aims. It presents a list of the features shared by all the Complex Systems involved in the 2030 Agenda. It shows the reasons why there are certain limitations in the prediction of Complex Systems' behaviors. It highlights that such limitations raise ethical issues whenever new technologies interfere with the dynamics of Complex Systems, such as human beings and the environment. Finally, new methodological approaches and promising research lines to face Complexity Challenges included in the 2030 Agenda are put forward.

Possible fates of the spread of SARS-CoV-2 in the Mexican context

The determination of the adequate time for house confinement and when social distancing restrictions should end are now two of the main challenges that any country has to face in an ongoing battle against SARS-CoV-2. The possibility of a new outbreak of the pandemic and how to avoid it is, nowadays, one of the primary objectives of epidemiological research. In this work, we present an innovative compartmental model that explicitly introduces the number of active cases, and employ it as a conceptual tool to explore the possible fates of the spread of SARS-CoV-2 in the Mexican context. We incorporated the impact of starting, inattention and end of restrictive social policies on the pandemic's time evolution via time-dependent corrections to the infection rates. The magnitude and impact on the epidemic due to post-social restrictive policies are also studied. The scenarios generated by the model could help authorities determine an adequate time and population load that may be allowed to reassume normal activities.

On Markov blankets and hierarchical self-organisation

Biological self-organisation can be regarded as a process of spontaneous pattern formation; namely, the emergence of structures that distinguish themselves from their environment. This process can occur at nested spatial scales: from the microscopic (e.g., the emergence of cells) to the macroscopic (e.g. the emergence of organisms). In this paper, we pursue the idea that Markov blankets - that separate the internal states of a structure from external states - can self-assemble at successively higher levels of organisation. Using simulations, based on the principle of variational free energy minimisation, we show that hierarchical self-organisation emerges when the microscopic elements of an ensemble have prior (e.g., genetic) beliefs that they participate in a macroscopic Markov blanket: i.e., they can only influence - or be influenced by - a subset of other elements. Furthermore, the emergent structures look very much like those found in nature (e.g., cells or organelles), when influences are mediated by short range signalling. These simulations are offered as a proof of concept that hierarchical self-organisation of Markov blankets (into Markov blankets) can explain the self-evidencing, autopoietic behaviour of biological systems.

Effects of graphene plates' adoption on the microstructure, mechanical properties, and in vivo biocompatibility of calcium silicate coating

Calcium silicate (CS) ceramic is a good coating candidate for biomedical implants to improve biocompatibility and accelerate early osseointegration. However, the poor fracture toughness and wear resistance of this ceramic material restricts the long-term performance of implants. In this study, graphene plates (GPs) were used as reinforcement to improve the mechanical properties of CS coating. Composite coating containing 1.5 weight % GPs was prepared by vacuum plasma spraying technology. The good survival of the GPs in the composite coating was demonstrated by Raman analysis, although the defects of the GPs were increased after plasma spraying. Effects of the GPs’ adoption on the microstructure of the coating were studied by scanning electron microscopy and transmission electron microscopy. Results showed that the GPs were homogenously distributed in the CS grains interface or enwrapped on the particles, and exhibited good wetting behavior with the CS matrix. The wear properties of the composite coating were obviously enhanced by the reinforcement of GPs. The reinforcement mechanism was attributed to the enhanced micro-hardness and interfacial bonding of the particles in the coating. In vivo experiments demonstrated that the composite coating possessed similarly good biocompatibility compared to pure CS coating. The bone-implant contact ratio reached 84.3%±7.4% for GPs/CS coating and 79.6%±9.4% for CS coating after 3 months’ implantation.