Criticality and universality in neuronal cultures during "up" and "down" states.

The brain can be seen as a self-organized dynamical system that optimizes information processing and storage capabilities. This is supported by studies across scales, from small neuronal assemblies to the whole brain, where neuronal activity exhibits features typically associated with phase transitions in statistical physics. Such a critical state is characterized by the emergence of scale-free statistics as captured, for example, by the sizes and durations of activity avalanches corresponding to a cascading process of information flow. Another phenomenon observed during sleep, under anesthesia, and in in vitro cultures, is that cortical and hippocampal neuronal networks alternate between "up" and "down" states characterized by very distinct firing rates. Previous theoretical work has been able to relate these two concepts and proposed that only up states are critical whereas down states are subcritical, also indicating that the brain spontaneously transitions between the two. Using high-speed high-resolution calcium imaging recordings of neuronal cultures, we test this hypothesis here by analyzing the neuronal avalanche statistics in populations of thousands of neurons during "up" and "down" states separately. We find that both "up" and "down" states can exhibit scale-free behavior when taking into account their intrinsic time scales. In particular, the statistical signature of "down" states is indistinguishable from those observed previously in cultures without "up" states. We show that such behavior can not be explained by network models of non-conservative leaky integrate-and-fire neurons with short-term synaptic depression, even when realistic noise levels, spatial network embeddings, and heterogeneous populations are taken into account, which instead exhibits behavior consistent with previous theoretical models. Similar differences were also observed when taking into consideration finite-size scaling effects, suggesting that the intrinsic dynamics and self-organization mechanisms of these cultures might be more complex than previously thought. In particular, our findings point to the existence of different mechanisms of neuronal communication, with different time scales, acting during either high-activity or low-activity states, potentially requiring different plasticity mechanisms.

Self-organized Patterns in Non-reciprocal Active Droplet Systems.

Non-equilibrium patterns are widespread in nature and often arise from the self-organization of constituents through nonreciprocal chemotactic interactions. In this study, we demonstrate how active oil-in-water droplet mixtures with predator-prey interactions can result in a variety of self-organized patterns. By manipulating physical parameters, the droplet diameter ratio and number ratio, we identify distinct classes of patterns within a binary droplet system, rationalize the pattern formation, and quantify motilities. Experimental results are recapitulated in numerical simulations using a minimal computational model that solely incorporates chemotactic interactions and steric repulsion among the constituents. The time evolution of the patterns is investigated and chemically explained. We also investigate how patterns vary with differing interaction strength by altering surfactant composition. Leveraging insights from the binary droplet system, the framework is extended to a ternary droplet mixture composed of multiple chasing droplet pairs to create chemically directed hierarchical organization. Our findings demonstrate how rationalizable, self-organized patterns can be programmed in a chemically minimal system and provide the basis for exploration of emergent organization and higher order complexity in active colloids.

Versatile system cores as a conceptual basis for generality in cell and developmental biology.

The discovery of general principles underlying the complexity and diversity of cellular and developmental systems is a central and long-standing aim of biology. While new technologies collect data at an ever-accelerating rate, there is growing concern that conceptual progress is not keeping pace. We contend that this is due to a paucity of conceptual frameworks that support meaningful generalizations. This led us to develop the core and periphery (C&P) hypothesis, which posits that many biological systems can be decomposed into a highly versatile core with a large behavioral repertoire and a specific periphery that configures said core to perform one particular function. Versatile cores tend to be widely reused across biology, which confers generality to theories describing them. Here, we introduce this concept and describe examples at multiple scales, including Turing patterning, actomyosin dynamics, multi-cellular morphogenesis, and vertebrate gastrulation. We also sketch its evolutionary basis and discuss key implications and open questions. We propose that the C&P hypothesis could unlock new avenues of conceptual progress in mesoscale biology.

Leaderless consensus decision-making determines cooperative transport direction in weaver ants.

Animal groups need to achieve and maintain consensus to minimize conflict among individuals and prevent group fragmentation. An excellent example of a consensus challenge is cooperative transport, where multiple individuals cooperate to move a large item together. This behaviour, regularly displayed by ants and humans only, requires individuals to agree on which direction to move in. Unlike humans, ants cannot use verbal communication but most likely rely on private information and/or mechanical forces sensed through the carried item to coordinate their behaviour. Here, we investigated how groups of weaver ants achieve consensus during cooperative transport using a tethered-object protocol, where ants had to transport a prey item that was tethered in place with a thin string. This protocol allows the decoupling of the movement of informed ants from that of uninformed individuals. We showed that weaver ants pool together the opinions of all group members to increase their navigational accuracy. We confirmed this result using a symmetry-breaking task, in which we challenged ants with navigating an open-ended corridor. Weaver ants are the first reported ant species to use a 'wisdom-of-the-crowd' strategy for cooperative transport, demonstrating that consensus mechanisms may differ according to the ecology of each species.

Correspondence between multiple signaling and developmental cellular patterns: a computational perspective.

The spatial arrangement of variant phenotypes during stem cell division plays a crucial role in the self-organization of cell tissues. The patterns observed in these cellular assemblies, where multiple phenotypes vie for space and resources, are largely influenced by a mixture of different diffusible chemical signals. This complex process is carried out within a chronological framework of interplaying intracellular and intercellular events. This includes receiving external stimulants, whether secreted by other individuals or provided by the environment, interpreting these environmental signals, and incorporating the information to designate cell fate. Here, given two distinct signaling patterns generated by Turing systems, we investigated the spatial distribution of differentiating cells that use these signals as external cues for modifying the production rates. By proposing a computational map, we show that there is a correspondence between the multiple signaling and developmental cellular patterns. In other words, the model provides an appropriate prediction for the final structure of the differentiated cells in a multi-signal, multi-cell environment. Conversely, when a final snapshot of cellular patterns is given, our algorithm can partially identify the signaling patterns that influenced the formation of the cellular structure, provided that the governing dynamic of the signaling patterns is already known.

Selection in molecular evolution.

Evolution requires selection. Molecular/chemical/preDarwinian evolution is no exception. One molecule must be selected over another for molecular evolution to occur and advance. Evolution, however, has no goal. The laws of physics have no utilitarian desire, intent or proficiency. Laws and constraints are blind to "usefulness." How then were potential multi-step processes anticipated, valued and pursued by inanimate nature? Can orchestration of formal systems be physico-chemically spontaneous? The purely physico-dynamic self-ordering of Chaos Theory and irreversible non-equilibrium thermodynamic "engines of disequilibria conversion" achieve neither orchestration nor formal organization. Natural selection is a passive and after-the-fact-of-life selection. Darwinian selection reduces to the differential survival and reproduction of the fittest already-living organisms. In the case of abiogenesis, selection had to be 1) Active, 2) Pre-Function, and 3) Efficacious. Selection had to take place at the molecular level prior to the existence of non-trivial functional processes. It could not have been passive or secondary. What naturalistic mechanisms might have been at play?

Beyond grassland degradation: Pathways to resilience for pastoralist households in alpine grassland ecosystems.

Sustaining the development of rural and pastoral communities' hinges on livelihood resilience. Pastoralist household resilience relies on resource availability and decision-making abilities. Despite extensive studies on pastoralist livelihoods, a significant knowledge gap remains in understanding the nuanced adaptive capacities of diverse households, particularly amid grassland degradation. Thus, this study investigates the household-based livelihood resilience of pastoralists in China's Three-River Headwater Region, offering policy recommendations for resilient livelihoods. Using stratified random sampling, 758 pastoralist household heads underwent semi-structured interviews to collect data. Five household characteristics, encompassing age, gender, energy use, well-being perception, and multi-household grazing participation, were evaluated. Looking ot the nature of data, descriptive statistics and non-parametric tests were performed in this study to draw the valid inferences. The results revealed a positive correlation (p < 0.05) between household head age and livelihood resilience, with divergent resilience across age groups. Varied energy usage yielded distinct impacts; households employing solar or mixed energy sources exhibited heightened resilience (p < 0.05). Household well-being emerged as an invariant variable concerning resilience. Furthermore, engagement in multi-household grazing (an informal institution) significantly (p < 0.05) influenced pastoralist livelihood resilience. These insights advocate targeted support for young household heads and the adoption of clean energy. Exploring the deeper strategies and mechanisms of multi-household grazing can enhance understanding and policy integration, guiding eco-friendly progress within rustic landscapes for pastoral communities.

Evolving through multiple, co-existing pressures to change: a case study of self-organization in primary care during the COVID-19 pandemic in Canada.

BACKGROUND: Primary care is often described as slow to change. But conceptualized through complexity theory, primary care is continually changing in unpredictable, non-linear ways through self-organization processes. Self-organization has proven hard to study directly. We aimed to develop a methodology to study self-organization and describe how a primary care clinic self-organizes over time. METHODOLOGY: We completed a virtual case study of an urban primary care clinic from May-Nov 2021, applying methodological insights from actor-network theory to examine the complexity theory concept of self-organization. We chose to focus our attention on self-organization activities that alter organizational routines. Data included fieldnotes of observed team meetings, document collection, interviews with clinic members, and notes from brief weekly discussions to detect actions to change clinical and administrative routines. Adapting schema analysis, we described changes to different organizational routines chronologically, then explored intersecting changes. We sought feedback on results from the participating clinic. FINDINGS: Re-establishing equilibrium remained challenging well into the COVID-19 pandemic. The primary care clinic continued to self-organize in response to changing health policies, unintended consequences of earlier adaptations, staff changes, and clinical care initiatives. Physical space, technologies, external and internal policies, guidelines, and clinic members all influenced self-organization. Changing one created ripple effects, sometimes generating new, unanticipated problems. Member checking confirmed we captured most of the changes to organizational routines during the case study period. CONCLUSIONS: Through insights from actor-network theory, applied to studying actions taken that alter organizational routines, it is possible to operationalize the theoretical construct of self-organization. Our methodology illuminates the primary care clinic as a continually changing entity with co-existing and intersecting processes of self-organization in response to varied change pressures.

Pattern Formation and Bistability in a Synthetic Intercellular Genetic Toggle.

Differentiation within multicellular organisms is a complex process that helps to establish spatial patterning and tissue formation within the body. Often, the differentiation of cells is governed by morphogens and intercellular signaling molecules that guide the fate of each cell, frequently using toggle-like regulatory components. Synthetic biologists have long sought to recapitulate patterned differentiation with engineered cellular communities, and various methods for differentiating bacteria have been invented. Here, we couple a synthetic corepressive toggle switch with intercellular signaling pathways to create a "quorum-sensing toggle". We show that this circuit not only exhibits population-wide bistability in a well-mixed liquid environment but also generates patterns of differentiation in colonies grown on agar containing an externally supplied morphogen. If coupled to other metabolic processes, circuits such as the one described here would allow for the engineering of spatially patterned, differentiated bacteria for use in biomaterials and bioelectronics.

Morphogenic Modeling of Corrosion Reveals Complex Effects of Intermetallic Particles.

Corrosion processes are often discussed as stochastic events. Here, it is shown that some of these seemingly random processes are not driven by nanoscopic fluctuations but rather by the spatial distribution of micrometer-scale heterogeneities that trigger fast reactions associated with corrosion. Using a novel excitable reaction-diffusion model, corrosion waves traveling over the metal surface and the associated material loss are described. This resulting nonuniform corrosion penetration, seen as a height loss in modeling, exposes buried intermetallic particles, which depending on the local electrochemical state of the surface trigger or block new waves. Informed by quantitative experimental data for the Mg-Al-Zn alloy AZ31B, wave speeds, wave widths, and average material loss are accurately captured. Morphogenic mitigation based on wave-breaking microparticles is also simulated. While AZ31B corrosion is identified as a process driven by rare-wave events, this study predicts several other corrosion regimes that proceed via spots or patchy patterns, opening the door for new protection, design, and prediction strategies.

Positional Information-Based Organization of Surfactant Droplet Swarms Emerging from Competition Between Local and Global Marangoni Effects.

Positional information is key for particles to adapt their behavior based on their position in external concentration gradients, and thereby self-organize into complex patterns. Here, position-dependent behavior of floating surfactant droplets that self-organize in a pH gradient is demonstrated, using the Marangoni effect to translate gradients of surface-active molecules into motion. First, fields of surfactant microliter-droplets are generated, in which droplets floating on water drive local, outbound Marangoni flows upon dissolution of surfactant and concomitantly grow myelin filaments. Next, a competing surfactant based on a hydrolysable amide is introduced, which is more surface active than the myelin surfactant and thereby inhibits the local Marangoni flows and myelin growth from the droplets. Upon introducing a pH gradient, the amide surfactant hydrolyses in the acidic region, so that the local Marangoni flows and myelin growth are reestablished. The resulting combination of local and global surface tension gradients produces a region of myelin-growing droplets and a region where myelin growth is suppressed, separated by a wave front of closely packed droplets, of which the position can be controlled by the pH gradient. Thereby, it is shown how "French flag"-patterns, in synthetic settings typically emerging from reaction-diffusion systems, can also be established via surfactant droplet systems.

Self-extinguishing relay waves enable homeostatic control of human neutrophil swarming.

Neutrophils collectively migrate to sites of injury and infection. How these swarms are coordinated to ensure the proper level of recruitment is unknown. Using an ex vivo model of infection, we show that human neutrophil swarming is organized by multiple pulsatile chemoattractant waves. These waves propagate through active relay in which stimulated neutrophils trigger their neighbors to release additional swarming cues. Unlike canonical active relays, we find these waves to be self-terminating, limiting the spatial range of cell recruitment. We identify an NADPH-oxidase-based negative feedback loop that is needed for this self-terminating behavior. We observe near-constant levels of neutrophil recruitment over a wide range of starting conditions, revealing surprising robustness in the swarming process. This homeostatic control is achieved by larger and more numerous swarming waves at lower cell densities. We link defective wave termination to a broken recruitment homeostat in the context of human chronic granulomatous disease.

Controlled Protein-Membrane Interactions Modulate Self-Organization of Min Protein Patterns.

Self-organizing protein patterns are crucial for living systems, governing important cellular processes such as polarization and division. While the field of protein self-organization has reached a point where basic pattern-forming mechanisms can be reconstituted in vitro using purified proteins, understanding how cells can dynamically switch and modulate these patterns, especially when transiently needed, remains an interesting frontier. Here, we demonstrate the efficient regulation of self-organizing protein patterns through the modulation of simple biophysical membrane parameters. Our investigation focuses on the impact of membrane affinity changes on Min protein patterns at lipid membranes composed of Escherichia coli lipids or minimal lipid compositions, and we present three major results. First, we observed the emergence of a diverse array of pattern phenotypes, ranging from waves over flower-shaped patterns to snowflake-like structures. Second, we demonstrated the dependency of these patterns on the density of protein-membrane linkers. Finally, we demonstrate that the shape of snowflake-like patterns is fine-tuned by membrane charge. Our results demonstrate the significant influence of membrane linkage as a straightforward biophysical parameter governing protein pattern formation. Our research points towards a simple yet intriguing mechanism by which cells can adeptly tune and switch protein patterns on the mesoscale.

Emergent scale-free networks.

Many complex systems-from the Internet to social, biological, and communication networks-are thought to exhibit scale-free structure. However, prevailing explanations require that networks grow over time, an assumption that fails in some real-world settings. Here, we explain how scale-free structure can emerge without growth through network self-organization. Beginning with an arbitrary network, we allow connections to detach from random nodes and then reconnect under a mixture of preferential and random attachment. While the numbers of nodes and edges remain fixed, the degree distribution evolves toward a power-law with an exponent γ = 1 + 1 p that depends only on the proportion p of preferential (rather than random) attachment. Applying our model to several real networks, we infer p directly from data and predict the relationship between network size and degree heterogeneity. Together, these results establish how scale-free structure can arise in networks of constant size and density, with broad implications for the structure and function of complex systems.

Self-organization underlies developmental robustness in plants.

Development is a self-organized process that builds on cells and their interactions. Cells are heterogeneous in gene expression, growth, and division; yet how development is robust despite such heterogeneity is a fascinating question. Here, we review recent progress on this topic, highlighting how developmental robustness is achieved through self-organization. We will first discuss sources of heterogeneity, including stochastic gene expression, heterogeneity in growth rate and direction, and heterogeneity in division rate and precision. We then discuss cellular mechanisms that buffer against such noise, including Paf1C- and miRNA-mediated denoising, spatiotemporal growth averaging and compensation, mechanisms to improve cell division precision, and coordination of growth rate and developmental timing between different parts of an organ. We also discuss cases where such heterogeneity is not buffered but utilized for development. Finally, we highlight potential directions for future studies of noise and developmental robustness.

Linking discrete and continuous models of cell birth and migration.

Self-organization of individuals within large collectives occurs throughout biology. Mathematical models can help elucidate the individual-level mechanisms behind these dynamics, but analytical tractability often comes at the cost of biological intuition. Discrete models provide straightforward interpretations by tracking each individual yet can be computationally expensive. Alternatively, continuous models supply a large-scale perspective by representing the 'effective' dynamics of infinite agents, but their results are often difficult to translate into experimentally relevant insights. We address this challenge by quantitatively linking spatio-temporal dynamics of continuous models and individual-based data in settings with biologically realistic, time-varying cell numbers. Specifically, we introduce and fit scaling parameters in continuous models to account for discrepancies that can arise from low cell numbers and localized interactions. We illustrate our approach on an example motivated by zebrafish-skin pattern formation, in which we create a continuous framework describing the movement and proliferation of a single cell population by upscaling rules from a discrete model. Our resulting continuous models accurately depict ensemble average agent-based solutions when migration or proliferation act alone. Interestingly, the same parameters are not optimal when both processes act simultaneously, highlighting a rich difference in how combining migration and proliferation affects discrete and continuous dynamics.

Self-Organization of Polyurethane Ionomers Based on Organophosphorus-Branched Polyols.

Based on organophosphorus branched polyols (AEPAs) synthesized using triethanolamine (TEOA), ortho-phosphoric acid (OPA), and polyoxyethylene glycol with MW = 400 (PEG), vapor-permeable polyurethane ionomers (AEPA-PEG-PUs) were obtained. During the synthesis of AEPAs, the reaction of the OPA etherification with polyoxyethylene glycol was studied in a wide temperature range and at different molar ratios of the starting components. It turned out that OPA simultaneously undergoes a catalytically activated etherification reaction with triethanolamine and PEG. After TEOA is fully involved in the etherification reaction, excess OPA does not react with the terminal hydroxyl groups of AEPA-PEG or the remaining amount of PEG. The ortho-phosphoric acid remaining in an unreacted state is involved in associative interactions with the phosphate ions of the AEPA. Increasing the synthesis temperature from 40 °C to 110 °C leads to an increase in OPA conversion. However, for the AEPA-PEG-PU based on AEPA-PEG obtained at 100 °C and 110 °C, ortho-phosphoric acid no longer enters into associative interactions with the phosphate ions of the AEPA. Due to the hydrophilicity of polyoxyethylene glycol, the presence of phosphate ions in the polyurethane structure, and their associative binding with the unreacted ortho-phosphoric acid, the diffusion of water molecules in polyurethanes is enhanced, and high values of vapor permeability and tensile strength were achieved.

Recapitulation and investigation of human brain development with neural organoids.

Organoids are 3D cultured tissues derived from stem cells that resemble the structure of living organs. Based on the accumulated knowledge of neural development, neural organoids that recapitulate neural tissue have been created by inducing self-organized neural differentiation of stem cells. Neural organoid techniques have been applied to human pluripotent stem cells to differentiate 3D human neural tissues in culture. Various methods have been developed to generate neural tissues of different regions. Currently, neural organoid technology has several significant limitations, which are being overcome in an attempt to create neural organoids that more faithfully recapitulate the living brain. The rapidly advancing neural organoid technology enables the use of living human neural tissue as research material and contributes to our understanding of the development, structure and function of the human nervous system, and is expected to be used to overcome neurological diseases and for regenerative medicine.

Beyond Conventional Enhancements: Self-Organization of a Buffer Material on Tin Oxide as a Game-Changer for Improving the Performance of Inverted Organic Solar Cells.

Inverted organic solar cells (OSCs) have garnered significant interest due to their remarkable stability. In this study, the efficiency and stability of inverted OSCs are enhanced via the in situ self-organization (SO) of an interfacial modification material Phen-NaDPO onto tin oxide (SnO2). During the device fabrication, Phen-NaDPO is spin-coated with the active materials all together on SnO2. Driven by the interactions with SnO2 and the thermodynamic forces due to its high surface energy and the convection flow, Phen-NaDPO spontaneously migrates to the SnO2 interface, resulting in the formation of an in situ modification layer on SnO2. This self-organization of Phen-NaDPO not only effectively reduces the work function of SnO2, but also enhances the ordered molecular stacking and manipulates the vertical morphology of the active layer, which suppress the surface trap-assisted recombination and minimize the charge extraction. As a result, the SO devices based on PM6:Y6 exhibit significantly improved photovoltaic performance with an enhanced power conversion efficiency of 17.62%. Moreover, the stability of the SO device is also improved. Furthermore, the SO ternary devices based on PM6:D18:L8-BO achieved an impressive PCE of 18.87%, standing as one of the highest values for single-junction inverted organic solar cells to date.

On the origin of life on earth.

The creation of the universe out of nothing (ex nihilo) is attributable to the eternal God. Would a direct divine intervention be needed for other singular events, such as the origin of life? Taking apart the human being, created to image and resemblance of God, we argue that current scientific knowledge allows us to rationally admit a continuity between the origins of the universe and the emergence of life on Earth. Although the irruption of living beings from inert matter is a leap or discontinuity in creation, a direct intervention of God would not be indispensable. The initial impulse of creation, with matter and energy in a space-time imbalance, could have triggered reactions between the different elements and a self-organization of metabolites, in accordance with natural physical-chemistry laws. This paradoxical increase of complexity ended with a transition from chemistry to biology. It happened when independence, metabolism, heritability, and life cycle took place in a protocellular unit. In this way, the emergence of life on earth could be part of an evolutionary dynamic of the timeless God's creative act.