Network representation of multicellular activity in pancreatic islets: Technical considerations for functional connectivity analysis.

Within the islets of Langerhans, beta cells orchestrate synchronized insulin secretion, a pivotal aspect of metabolic homeostasis. Despite the inherent heterogeneity and multimodal activity of individual cells, intercellular coupling acts as a homogenizing force, enabling coordinated responses through the propagation of intercellular waves. Disruptions in this coordination are implicated in irregular insulin secretion, a hallmark of diabetes. Recently, innovative approaches, such as integrating multicellular calcium imaging with network analysis, have emerged for a quantitative assessment of the cellular activity in islets. However, different groups use distinct experimental preparations, microscopic techniques, apply different methods to process the measured signals and use various methods to derive functional connectivity patterns. This makes comparisons between findings and their integration into a bigger picture difficult and has led to disputes in functional connectivity interpretations. To address these issues, we present here a systematic analysis of how different approaches influence the network representation of islet activity. Our findings show that the choice of methods used to construct networks is not crucial, although care is needed when combining data from different islets. Conversely, the conclusions drawn from network analysis can be heavily affected by the pre-processing of the time series, the type of the oscillatory component in the signals, and by the experimental preparation. Our tutorial-like investigation aims to resolve interpretational issues, reconcile conflicting views, advance functional implications, and encourage researchers to adopt connectivity analysis. As we conclude, we outline challenges for future research, emphasizing the broader applicability of our conclusions to other tissues exhibiting complex multicellular dynamics.

Functional characteristics of hub and wave-initiator cells in ß cell networks.

Islets of Langerhans operate as multicellular networks in which several hundred ß cells work in synchrony to produce secretory pulses of insulin, a hormone crucial for controlling metabolic homeostasis. Their collective rhythmic activity is facilitated by gap junctional coupling and affected by their functional heterogeneity, but the details of this robust and coordinated behavior are still not fully understood. Recent advances in multicellular imaging and optogenetic and photopharmacological strategies, as well as in network science, have led to the discovery of specialized ß cell subpopulations that were suggested to critically determine the collective dynamics in the islets. In particular hubs, i.e., ß cells with many functional connections, are believed to significantly enhance communication capacities of the intercellular network and facilitate an efficient spreading of intercellular Ca2+ waves, whereas wave-initiator cells trigger intercellular signals in their cohorts. Here, we determined Ca2+ signaling characteristics of these two ß cell subpopulations and the relationship between them by means of functional multicellular Ca2+ imaging in mouse pancreatic tissue slices in combination with methods of complex network theory. We constructed network layers based on individual Ca2+ waves to identify wave initiators, and functional correlation-based networks to detect hubs. We found that both cell types exhibit a higher-than-average active time under both physiological and supraphysiological glucose concentrations, but also that they differ significantly in many other functional characteristics. Specifically, Ca2+ oscillations in hubs are more regular, and their role appears to be much more stable over time than for initiator cells. Moreover, in contrast to wave initiators, hubs transmit intercellular signals faster than other cells, which implies a stronger intercellular coupling. Our research indicates that hubs and wave-initiator cell subpopulations are both natural features of healthy pancreatic islets, but their functional roles in principle do not overlap and should thus not be considered equal.

Determinants of collective failure in excitable networks.

We study collective failures in biologically realistic networks that consist of coupled excitable units. The networks have broad-scale degree distribution, high modularity, and small-world properties, while the excitable dynamics is determined by the paradigmatic FitzHugh-Nagumo model. We consider different coupling strengths, bifurcation distances, and various aging scenarios as potential culprits of collective failure. We find that for intermediate coupling strengths, the network remains globally active the longest if the high-degree nodes are first targets for inactivation. This agrees well with previously published results, which showed that oscillatory networks can be highly fragile to the targeted inactivation of low-degree nodes, especially under weak coupling. However, we also show that the most efficient strategy to enact collective failure does not only non-monotonically depend on the coupling strength, but it also depends on the distance from the bifurcation point to the oscillatory behavior of individual excitable units. Altogether, we provide a comprehensive account of determinants of collective failure in excitable networks, and we hope this will prove useful for better understanding breakdowns in systems that are subject to such dynamics.

NMDA receptor inhibition increases, synchronizes, and stabilizes the collective pancreatic beta cell activity: Insights through multilayer network analysis.

NMDA receptors promote repolarization in pancreatic beta cells and thereby reduce glucose-stimulated insulin secretion. Therefore, NMDA receptors are a potential therapeutic target for diabetes. While the mechanism of NMDA receptor inhibition in beta cells is rather well understood at the molecular level, its possible effects on the collective cellular activity have not been addressed to date, even though proper insulin secretion patterns result from well-synchronized beta cell behavior. The latter is enabled by strong intercellular connectivity, which governs propagating calcium waves across the islets and makes the heterogeneous beta cell population work in synchrony. Since a disrupted collective activity is an important and possibly early contributor to impaired insulin secretion and glucose intolerance, it is of utmost importance to understand possible effects of NMDA receptor inhibition on beta cell functional connectivity. To address this issue, we combined confocal functional multicellular calcium imaging in mouse tissue slices with network science approaches. Our results revealed that NMDA receptor inhibition increases, synchronizes, and stabilizes beta cell activity without affecting the velocity or size of calcium waves. To explore intercellular interactions more precisely, we made use of the multilayer network formalism by regarding each calcium wave as an individual network layer, with weighted directed connections portraying the intercellular propagation. NMDA receptor inhibition stabilized both the role of wave initiators and the course of waves. The findings obtained with the experimental antagonist of NMDA receptors, MK-801, were additionally validated with dextrorphan, the active metabolite of the approved drug dextromethorphan, as well as with experiments on NMDA receptor KO mice. In sum, our results provide additional and new evidence for a possible role of NMDA receptor inhibition in treatment of type 2 diabetes and introduce the multilayer network paradigm as a general strategy to examine effects of drugs on connectivity in multicellular systems.

Glucose-dependent activation, activity, and deactivation of beta cell networks in acute mouse pancreas tissue slices.

Many details of glucose-stimulated intracellular calcium changes in ß cells during activation, activity, and deactivation, as well as their concentration-dependence, remain to be analyzed. Classical physiological experiments indicated that in islets, functional differences between individual cells are largely attenuated, but recent findings suggest considerable intercellular heterogeneity, with some cells possibly coordinating the collective responses. To address the above with an emphasis on heterogeneity and describing the relations between classical physiological and functional network properties, we performed functional multicellular calcium imaging in mouse pancreas tissue slices over a wide range of glucose concentrations. During activation, delays to activation of cells and any-cell-to-first-responder delays are shortened, and the sizes of simultaneously responding clusters increased with increasing glucose concentrations. Exactly the opposite characterized deactivation. The frequency of fast calcium oscillations during activity increased with increasing glucose up to 12 mM glucose concentration, beyond which oscillation duration became longer, resulting in a homogenous increase in active time. In terms of functional connectivity, islets progressed from a very segregated network to a single large functional unit with increasing glucose concentration. A comparison between classical physiological and network parameters revealed that the first-responders during activation had longer active times during plateau and the most active cells during the plateau tended to deactivate later. Cells with the most functional connections tended to activate sooner, have longer active times, and deactivate later. Our findings provide a common ground for recent differing views on ß cell heterogeneity and an important baseline for future studies of stimulus-secretion and intercellular coupling.NEW & NOTEWORTHY We assessed concentration-dependence in coupled ß cells, degree of functional heterogeneity, and uncovered possible specialized subpopulations during the different phases of the response to glucose at the level of many individual cells. To this aim, we combined acute mouse pancreas tissue slices with functional multicellular calcium imaging over a wide range from threshold (7 mM) and physiological (8 and 9 mM) to supraphysiological (12 and 16 mM) glucose concentrations, classical physiological, and advanced network analyses.

Modelling of energy-driven switch for glucagon and insulin secretion.

We present a mathematical model of the energy-driven metabolic switch for glucagon and insulin secretion from pancreatic alpha and beta cells, respectively. The energy status related to hormone secretion is studied for various glucose concentrations. Additionally, the physiological response is studied with regards to the presence of other metabolites, particularly the free-fatty acids. At low glucose, the ATP production in alpha cells is high due to free-fatty acids oxidation in mitochondria, which enables glucagon secretion. When the glucose concentration is elevated above the threshold value, the glucagon secretion is switched off due to the contribution of glycolytic ATP production, representing an "anaerobic switch". On the other hand, during hypoglycemia, the ATP production in beta cells is low, reflecting a "waiting state" for glucose as the main metabolite. When glucose is elevated above the threshold value, the oxidative fate of glucose in mitochondria is the main source of energy required for effective insulin secretion, i.e. the "aerobic switch". Our results show the importance of well-regulated and fine-tuned energetic processes in pancreatic alpha and beta cells required for efficient hormone secretion and hence effective blood glucose regulation. These energetic processes have to be appropriately switched on and off based on the sensing of different metabolites by alpha and beta cells. Our computational results indicate that disturbances in cell energetics (e.g. mitochondrial dysfunction), and dysfunctional metabolite sensing and distribution throughout the cell might be related to pathologies such as metabolic syndrome and diabetes.

The relationship between node degree and dissipation rate in networks of diffusively coupled oscillators and its significance for pancreatic beta cells.

Self-sustained oscillatory dynamics is a motion along a stable limit cycle in the phase space, and it arises in a wide variety of mechanical, electrical, and biological systems. Typically, oscillations are due to a balance between energy dissipation and generation. Their stability depends on the properties of the attractor, in particular, its dissipative characteristics, which in turn determine the flexibility of a given dynamical system. In a network of oscillators, the coupling additionally contributes to the dissipation, and hence affects the robustness of the oscillatory solution. Here, we therefore investigate how a heterogeneous network structure affects the dissipation rate of individual oscillators. First, we show that in a network of diffusively coupled oscillators, the dissipation is a linearly decreasing function of the node degree, and we demonstrate this numerically by calculating the average divergence of coupled Hopf oscillators. Subsequently, we use recordings of intracellular calcium dynamics in pancreatic beta cells in mouse acute tissue slices and the corresponding functional connectivity networks for an experimental verification of the presented theory. We use methods of nonlinear time series analysis to reconstruct the phase space and calculate the sum of Lyapunov exponents. Our analysis reveals a clear tendency of cells with a higher degree, that is, more interconnected cells, having more negative values of divergence, thus confirming our theoretical predictions. We discuss these findings in the context of energetic aspects of signaling in beta cells and potential risks for pathological changes in the tissue.

Membrane Potential and Calcium Dynamics in Beta Cells from Mouse Pancreas Tissue Slices: Theory, Experimentation, and Analysis.

Beta cells in the pancreatic islets of Langerhans are precise biological sensors for glucose and play a central role in balancing the organism between catabolic and anabolic needs. A hallmark of the beta cell response to glucose are oscillatory changes of membrane potential that are tightly coupled with oscillatory changes in intracellular calcium concentration which, in turn, elicit oscillations of insulin secretion. Both membrane potential and calcium changes spread from one beta cell to the other in a wave-like manner. In order to assess the properties of the abovementioned responses to physiological and pathological stimuli, the main challenge remains how to effectively measure membrane potential and calcium changes at the same time with high spatial and temporal resolution, and also in as many cells as possible. To date, the most wide-spread approach has employed the electrophysiological patch-clamp method to monitor membrane potential changes. Inherently, this technique has many advantages, such as a direct contact with the cell and a high temporal resolution. However, it allows one to assess information from a single cell only. In some instances, this technique has been used in conjunction with CCD camera-based imaging, offering the opportunity to simultaneously monitor membrane potential and calcium changes, but not in the same cells and not with a reliable cellular or subcellular spatial resolution. Recently, a novel family of highly-sensitive membrane potential reporter dyes in combination with high temporal and spatial confocal calcium imaging allows for simultaneously detecting membrane potential and calcium changes in many cells at a time. Since the signals yielded from both types of reporter dyes are inherently noisy, we have developed complex methods of data denoising that permit for visualization and pixel-wise analysis of signals. Combining the experimental approach of high-resolution imaging with the advanced analysis of noisy data enables novel physiological insights and reassessment of current concepts in unprecedented detail.

The influence of gap junction network complexity on pulmonary artery smooth muscle reactivity in normoxic and chronically hypoxic conditions.

Experiments on intrapulmonary arteries (IPAs) isolated from rats maintained in normoxia and chronic hypobaric hypoxia showed that in normoxia, the IPA contractile sensitivity to KCl was not modified by gap junction inhibition. In contrast, chronic hypoxia induced an endothelium-independent hypersensitivity, which was suppressed by gap junction inhibition. For the theoretical analysis of these results, we developed a model of interconnected myocytes. Given that smooth muscle cells in IPAs are known to communicate via gap junctions, we regard the cytoarchitecture of the IPA as a spatial network, in which nodes represent individual smooth muscle cells and the links signify intercellular communication. A single-cell model that drives the dynamics of individual nodes includes the major elements of voltage-dependent Ca(2+) signalling. In addition, interindividual variability of SMCs is introduced by distributing the reversal potentials for K(+). Cell-to-cell connection consists of passive Ca(2+) diffusion and electrical coupling, and connection between cells is determined by the topology of the intercellular network. Model predictions indicate that the experimental results can be explained by topological modifications and not by changes in the number of gap junctions. According to the model, in normoxia the myocytes are connected in a complex network, whereas chronic hypoxia is related to loss of complexity, leading to hypersensitivity. Our results thus indicate that chronic hypoxia entails gap junction network rearrangements, leading to disturbances in the intercellular communication pathways.

Functional connectivity in islets of Langerhans from mouse pancreas tissue slices.

We propose a network representation of electrically coupled beta cells in islets of Langerhans. Beta cells are functionally connected on the basis of correlations between calcium dynamics of individual cells, obtained by means of confocal laser-scanning calcium imaging in islets from acute mouse pancreas tissue slices. Obtained functional networks are analyzed in the light of known structural and physiological properties of islets. Focusing on the temporal evolution of the network under stimulation with glucose, we show that the dynamics are more correlated under stimulation than under non-stimulated conditions and that the highest overall correlation, largely independent of Euclidean distances between cells, is observed in the activation and deactivation phases when cells are driven by the external stimulus. Moreover, we find that the range of interactions in networks during activity shows a clear dependence on the Euclidean distance, lending support to previous observations that beta cells are synchronized via calcium waves spreading throughout islets. Most interestingly, the functional connectivity patterns between beta cells exhibit small-world properties, suggesting that beta cells do not form a homogeneous geometric network but are connected in a functionally more efficient way. Presented results provide support for the existing knowledge of beta cell physiology from a network perspective and shed important new light on the functional organization of beta cell syncitia whose structural topology is probably not as trivial as believed so far.

The role of anaplerotic metabolism of glucose and glutamine in insulin secretion: A model approach.

We propose a detailed computational beta cell model that emphasizes the role of anaplerotic metabolism under glucose and glucose-glutamine stimulation. This model goes beyond the traditional focus on mitochondrial oxidative phosphorylation and ATP-sensitive K+ channels, highlighting the predominant generation of ATP from phosphoenolpyruvate in the vicinity of KATP channels. It also underlines the modulatory role of H2O2 as a signaling molecule in the first phase of glucose-stimulated insulin secretion. In the second phase, the model emphasizes the critical role of anaplerotic pathways, activated by glucose stimulation via pyruvate carboxylase and by glutamine via glutamate dehydrogenase. It particularly focuses on the production of NADPH and glutamate as key enhancers of insulin secretion. The predictions of the model are consistent with empirical data, highlighting the complex interplay of metabolic pathways and emphasizing the primary role of glucose and the facilitating role of glutamine in insulin secretion. By delineating these crucial metabolic pathways, the model provides valuable insights into potential therapeutic targets for diabetes.

Modeling the seasonal adaptation of circadian clocks by changes in the network structure of the suprachiasmatic nucleus.

The dynamics of circadian rhythms needs to be adapted to day length changes between summer and winter. It has been observed experimentally, however, that the dynamics of individual neurons of the suprachiasmatic nucleus (SCN) does not change as the seasons change. Rather, the seasonal adaptation of the circadian clock is hypothesized to be a consequence of changes in the intercellular dynamics, which leads to a phase distribution of electrical activity of SCN neurons that is narrower in winter and broader during summer. Yet to understand this complex intercellular dynamics, a more thorough understanding of the impact of the network structure formed by the SCN neurons is needed. To that effect, we propose a mathematical model for the dynamics of the SCN neuronal architecture in which the structure of the network plays a pivotal role. Using our model we show that the fraction of long-range cell-to-cell connections and the seasonal changes in the daily rhythms may be tightly related. In particular, simulations of the proposed mathematical model indicate that the fraction of long-range connections between the cells adjusts the phase distribution and consequently the length of the behavioral activity as follows: dense long-range connections during winter lead to a narrow activity phase, while rare long-range connections during summer lead to a broad activity phase. Our model is also able to account for the experimental observations indicating a larger light-induced phase-shift of the circadian clock during winter, which we show to be a consequence of higher synchronization between neurons. Our model thus provides evidence that the variations in the seasonal dynamics of circadian clocks can in part also be understood and regulated by the plasticity of the SCN network structure.

Both electrical and metabolic coupling shape the collective multimodal activity and functional connectivity patterns in beta cell collectives: A computational model perspective.

Pancreatic beta cells are coupled excitable oscillators that synchronize their activity via different communication pathways. Their oscillatory activity manifests itself on multiple timescales and consists of bursting electrical activity, subsequent oscillations in the intracellular Ca^{2+}, as well as oscillations in metabolism and exocytosis. The coordination of the intricate activity on the multicellular level plays a key role in the regulation of physiological pulsatile insulin secretion and is incompletely understood. In this paper, we investigate theoretically the principles that give rise to the synchronized activity of beta cell populations by building up a phenomenological multicellular model that incorporates the basic features of beta cell dynamics. Specifically, the model is composed of coupled slow and fast oscillatory units that reflect metabolic processes and electrical activity, respectively. Using a realistic description of the intercellular interactions, we study how the combination of electrical and metabolic coupling generates collective rhythmicity and shapes functional beta cell networks. It turns out that while electrical coupling solely can synchronize the responses, the addition of metabolic interactions further enhances coordination, the spatial range of interactions increases the number of connections in the functional beta cell networks, and ensures a better consistency with experimental findings. Moreover, our computational results provide additional insights into the relationship between beta cell heterogeneity, their activity profiles, and functional connectivity, supplementing thereby recent experimental results on endocrine networks.

The effect of forskolin and the role of Epac2A during activation, activity, and deactivation of beta cell networks.

Beta cells couple stimulation by glucose with insulin secretion and impairments in this coupling play a central role in diabetes mellitus. Cyclic adenosine monophosphate (cAMP) amplifies stimulus-secretion coupling via protein kinase A and guanine nucleotide exchange protein 2 (Epac2A). With the present research, we aimed to clarify the influence of cAMP-elevating diterpene forskolin on cytoplasmic calcium dynamics and intercellular network activity, which are two of the crucial elements of normal beta cell stimulus-secretion coupling, and the role of Epac2A under normal and stimulated conditions. To this end, we performed functional multicellular calcium imaging of beta cells in mouse pancreas tissue slices after stimulation with glucose and forskolin in wild-type and Epac2A knock-out mice. Forskolin evoked calcium signals in otherwise substimulatory glucose and beta cells from Epac2A knock-out mice displayed a faster activation. During the plateau phase, beta cells from Epac2A knock-out mice displayed a slightly higher active time in response to glucose compared with wild-type littermates, and stimulation with forskolin increased the active time via an increase in oscillation frequency and a decrease in oscillation duration in both Epac2A knock-out and wild-type mice. Functional network properties during stimulation with glucose did not differ in Epac2A knock-out mice, but the presence of Epac2A was crucial for the protective effect of stimulation with forskolin in preventing a decline in beta cell functional connectivity with time. Finally, stimulation with forskolin prolonged beta cell activity during deactivation, especially in Epac2A knock-out mice.

Exendin-4 affects calcium signalling predominantly during activation and activity of beta cell networks in acute mouse pancreas tissue slices.

Tight control of beta cell stimulus-secretion coupling is crucial for maintaining homeostasis of energy-rich nutrients. While glucose serves as a primary regulator of this process, incretins augment beta cell function, partly by enhancing cytosolic [Ca2+] dynamics. However, the details of how precisely they affect beta cell recruitment during activation, their active time, and functional connectivity during plateau activity, and how they influence beta cell deactivation remain to be described. Performing functional multicellular Ca2+ imaging in acute mouse pancreas tissue slices enabled us to systematically assess the effects of the GLP-1 receptor agonist exendin-4 (Ex-4) simultaneously in many coupled beta cells with high resolution. In otherwise substimulatory glucose, Ex-4 was able to recruit approximately a quarter of beta cells into an active state. Costimulation with Ex-4 and stimulatory glucose shortened the activation delays and accelerated beta cell activation dynamics. More specifically, active time increased faster, and the time required to reach half-maximal activation was effectively halved in the presence of Ex-4. Moreover, the active time and regularity of [Ca2+]IC oscillations increased, especially during the first part of beta cell response. In contrast, subsequent addition of Ex-4 to already active cells did not significantly enhance beta cell activity. Network analyses further confirmed increased connectivity during activation and activity in the presence of Ex-4, with hub cell roles remaining rather stable in both control experiments and experiments with Ex-4. Interestingly, Ex-4 demonstrated a biphasic effect on deactivation, slightly prolonging beta cell activity at physiological concentrations and shortening deactivation delays at supraphysiological concentrations. In sum, costimulation by Ex-4 and glucose increases [Ca2+]IC during beta cell activation and activity, indicating that the effect of incretins may, to an important extent, be explained by enhanced [Ca2+]IC signals. During deactivation, previous incretin stimulation does not critically prolong cellular activity, which corroborates their low risk of hypoglycemia.

Interlayer Connectivity Affects the Coherence Resonance and Population Activity Patterns in Two-Layered Networks of Excitatory and Inhibitory Neurons.

The firing patterns of neuronal populations often exhibit emergent collective oscillations, which can display substantial regularity even though the dynamics of individual elements is very stochastic. One of the many phenomena that is often studied in this context is coherence resonance, where additional noise leads to improved regularity of spiking activity in neurons. In this work, we investigate how the coherence resonance phenomenon manifests itself in populations of excitatory and inhibitory neurons. In our simulations, we use the coupled FitzHugh-Nagumo oscillators in the excitable regime and in the presence of neuronal noise. Formally, our model is based on the concept of a two-layered network, where one layer contains inhibitory neurons, the other excitatory neurons, and the interlayer connections represent heterotypic interactions. The neuronal activity is simulated in realistic coupling schemes in which neurons within each layer are connected with undirected connections, whereas neurons of different types are connected with directed interlayer connections. In this setting, we investigate how different neurophysiological determinants affect the coherence resonance. Specifically, we focus on the proportion of inhibitory neurons, the proportion of excitatory interlayer axons, and the architecture of interlayer connections between inhibitory and excitatory neurons. Our results reveal that the regularity of simulated neural activity can be increased by a stronger damping of the excitatory layer. This can be accomplished with a higher proportion of inhibitory neurons, a higher fraction of inhibitory interlayer axons, a stronger coupling between inhibitory axons, or by a heterogeneous configuration of interlayer connections. Our approach of modeling multilayered neuronal networks in combination with stochastic dynamics offers a novel perspective on how the neural architecture can affect neural information processing and provide possible applications in designing networks of artificial neural circuits to optimize their function via noise-induced phenomena.

Computational modeling of targeted temperature management in post-cardiac arrest patients.

Our core body temperature is held around [Formula: see text]C by an effective internal thermoregulatory system. However, various clinical scenarios have a more favorable outcome under external temperature regulation. Therapeutic hypothermia, for example, was found beneficial for the outcome of resuscitated cardiac arrest patients due to its protection against cerebral ischemia. Nonetheless, practice shows that outcomes of targeted temperature management vary considerably in dependence on individual tissue damage levels and differences in therapeutic strategies and protocols. Here, we address these differences in detail by means of computational modeling. We develop a multi-segment and multi-node thermoregulatory model that takes into account details related to specific post-cardiac arrest-related conditions, such as thermal imbalances due to sedation and anesthesia, increased metabolic rates induced by inflammatory processes, and various external cooling techniques. In our simulations, we track the evolution of the body temperature in patients subjected to post-resuscitation care, with particular emphasis on temperature regulation via an esophageal heat transfer device, on the examination of the alternative gastric cooling with ice slurry, and on how anesthesia and the level of inflammatory response influence thermal behavior. Our research provides a better understanding of the heat transfer processes and therapies used in post-cardiac arrest patients.

Networks behind the morphology and structural design of living systems.

Technological advances in imaging techniques and biometric data acquisition have enabled us to apply methods of network science to study the morphology and structural design of organelles, organs, and tissues, as well as the coordinated interactions among them that yield a healthy physiology at the level of whole organisms. We here review research dedicated to these advances, in particular focusing on networks between cells, the topology of multicellular structures, neural interactions, fluid transportation networks, and anatomical networks. The percolation of blood vessels, structural connectivity within the brain, the porous structure of bones, and relations between different anatomical parts of the human body are just some of the examples that we explore in detail. We argue and show that the models, methods, and algorithms developed in the realm of network science are ushering in a new era of network-based inquiry into the morphology and structural design of living systems in the broadest possible terms. We also emphasize that the need and applicability of this research is likely to increase significantly in the years to come due to the rapid progress made in the development of bioartificial substitutes and tissue engineering.

Ca2+ Oscillations, Waves, and Networks in Islets From Human Donors With and Without Type 2 Diabetes.

Pancreatic islets are highly interconnected structures that produce pulses of insulin and other hormones, maintaining normal homeostasis of glucose and other nutrients. Normal stimulus-secretion and intercellular coupling are essential to regulated secretory responses, and these hallmarks are known to be altered in diabetes. In the current study, we used calcium imaging of isolated human islets to assess their collective behavior. The activity occurred in the form of calcium oscillations, was synchronized across different regions of islets through calcium waves, and was glucose dependent: higher glucose enhanced the activity, elicited a greater proportion of global calcium waves, and led to denser and less fragmented functional networks. Hub regions were identified in stimulatory conditions, and they were characterized by long active times. Moreover, calcium waves were found to be initiated in different subregions and the roles of initiators and hubs did not overlap. In type 2 diabetes, glucose dependence was retained, but reduced activity, locally restricted waves, and more segregated networks were detected compared with control islets. Interestingly, hub regions seemed to suffer the most by losing a disproportionately large fraction of connections. These changes affected islets from donors with diabetes in a heterogeneous manner.

pH-Dependence of Glucose-Dependent Activity of Beta Cell Networks in Acute Mouse Pancreatic Tissue Slice.

Extracellular pH has the potential to affect various aspects of the pancreatic beta cell function. To explain this effect, a number of mechanisms was proposed involving both extracellular and intracellular targets and pathways. Here, we focus on reassessing the influence of extracellular pH on glucose-dependent beta cell activation and collective activity in physiological conditions. To this end we employed mouse pancreatic tissue slices to perform high-temporally resolved functional imaging of cytosolic Ca2+ oscillations. We investigated the effect of either physiological H+ excess or depletion on the activation properties as well as on the collective activity of beta cell in an islet. Our results indicate that lowered pH invokes activation of a subset of beta cells in substimulatory glucose concentrations, enhances the average activity of beta cells, and alters the beta cell network properties in an islet. The enhanced average activity of beta cells was determined indirectly utilizing cytosolic Ca2+ imaging, while direct measuring of insulin secretion confirmed that this enhanced activity is accompanied by a higher insulin release. Furthermore, reduced functional connectivity and higher functional segregation at lower pH, both signs of a reduced intercellular communication, do not necessary result in an impaired insulin release.