Neuronal Interactions Research Articles

Development of brain organoid technology derived from iPSC for the neurodegenerative disease modelling: a glance through.

Neurodegenerative diseases are adult-onset neurological conditions that are notoriously difficult to model for drug discovery and development because most models are unable to accurately recapitulate pathology in disease-relevant cells, making it extremely difficult to explore the potential mechanisms underlying neurodegenerative diseases. Therefore, alternative models of human or animal cells have been developed to bridge the gap and allow the impact of new therapeutic strategies to be anticipated more accurately by trying to mimic neuronal and glial cell interactions and many more mechanisms. In tandem with the emergence of human-induced pluripotent stem cells which were first generated in 2007, the accessibility to human-induced pluripotent stem cells (hiPSC) derived from patients can be differentiated into disease-relevant neurons, providing an unrivaled platform for in vitro modeling, drug testing, and therapeutic strategy development. The recent development of three-dimensional (3D) brain organoids derived from iPSCs as the best alternative models for the study of the pathological features of neurodegenerative diseases. This review highlights the overview of current iPSC-based disease modeling and recent advances in the development of iPSC models that incorporate neurodegenerative diseases. In addition, a summary of the existing brain organoid-based disease modeling of Alzheimer's disease was presented. We have also discussed the current methodologies of regional specific brain organoids modeled, its potential applications, emphasizing brain organoids as a promising platform for the modeling of patient-specific diseases, the development of personalized therapies, and contributing to the design of ongoing or future clinical trials on organoid technologies.

Emergent dynamics in an astrocyte-neuronal network coupled via nitric oxide

In the brain, both neurons and glial cells work in conjunction with each other during information processing. Stimulation of neurons can induce calcium oscillations in astrocytes which in turn can affect neuronal calcium dynamics. The ‘glissandi’ effect is one such phenomenon, associated with a decrease in infraslow fluctuations, in which synchronized calcium oscillations propagate as a wave in hundreds of astrocytes. Nitric oxide molecules released from the astrocytes contribute to synaptic functions based on the underlying astrocyte–neuron interaction network. In this study, by defining an astrocyte–neuronal (A–N) calcium unit as an integrated circuit of one neuron and one astrocyte, we developed a minimal model of neuronal stimulus-dependent and NO-mediated emergence of calcium waves in astrocytes. Incorporating inter-unit communication via NO molecules, a coupled network of 1000 such A–N calcium units is developed in which multiple stable regimes were found to emerge in astrocytes. We examined the ranges of neuronal stimulus strength and the coupling strength between A–N calcium units that give rise to such dynamical behaviors. We also report that there exists a range of coupling strength, wherein units not receiving stimulus also start showing oscillations and become synchronized. Our results support the hypothesis that glissandi-like phenomena exhibiting synchronized calcium oscillations in astrocytes help in efficient synaptic transmission by reducing the energy demand of the process.

Modelling the emergence of synchrony from decentralized rhythmic interactions in animal communication.

To communicate, an animal's strategic timing of rhythmic signals is crucial. Evolutionary, game-theoretical, and dynamical systems models can shed light on the interaction between individuals and the associated costs and benefits of signalling at a specific time. Mathematical models that study rhythmic interactions from a strategic or evolutionary perspective are rare in animal communication research. But new inspiration may come from a recent game theory model of how group synchrony emerges from local interactions of oscillatory neurons. In the study, the authors analyse when the benefit of joint synchronization outweighs the cost of individual neurons sending electrical signals to each other. They postulate there is a benefit for pairs of neurons to fire together and a cost for a neuron to communicate. The resulting model delivers a variant of a classical dynamical system, the Kuramoto model. Here, we present an accessible overview of the Kuramoto model and evolutionary game theory, and of the 'oscillatory neurons' model. We interpret the model's results and discuss the advantages and limitations of using this particular model in the context of animal rhythmic communication. Finally, we sketch potential future directions and discuss the need to further combine evolutionary dynamics, game theory and rhythmic processes in animal communication studies.

Activity-Dependent Transcriptional Program in NGN2+ Neurons Enriched for Genetic Risk for Brain-Related Disorders

BackgroundConverging evidence from large-scale genetic and postmortem studies highlights the role of aberrant neurotransmission and genetic regulation in brain-related disorders. However, identifying neuronal activity–regulated transcriptional programs in the human brain and understanding how changes contribute to disease remain challenging. MethodsTo better understand how the activity-dependent regulome contributes to risk for brain-related disorders, we profiled the transcriptomic and epigenomic changes following neuronal depolarization in human induced pluripotent stem cell–derived glutamatergic neurons (NGN2) from 6 patients with schizophrenia and 5 control participants. ResultsMultiomic data integration associated global patterns of chromatin accessibility with gene expression and identified enhancer-promoter interactions in glutamatergic neurons. Within 1 hour of potassium chloride–induced depolarization, independent of diagnosis, glutamatergic neurons displayed substantial activity-dependent changes in the expression of genes regulating synaptic function. Depolarization-induced changes in the regulome revealed significant heritability enrichment for schizophrenia and Parkinson’s disease, adding to mounting evidence that sequence variation within activation-dependent regulatory elements contributes to the genetic risk for brain-related disorders. Gene coexpression network analysis elucidated interactions among activity-dependent and disease-associated genes and pointed to a key driver (NAV3) that interacted with multiple genes involved in axon guidance. ConclusionsOverall, we demonstrated that deciphering the activity-dependent regulome in glutamatergic neurons reveals novel targets for advanced diagnosis and therapy.

A spatially distributed model of brain metabolism highlights the role of diffusion in brain energy metabolism

The different active roles of neurons and astrocytes during neuronal activation are associated with the metabolic processes necessary to supply the energy needed for their respective tasks at rest and during neuronal activation. Metabolism, in turn, relies on the delivery of metabolites and removal of toxic byproducts through diffusion processes and the cerebral blood flow. A comprehensive mathematical model of brain metabolism should account not only for the biochemical processes and the interaction of neurons and astrocytes, but also the diffusion of metabolites. In the present article, we present a computational methodology based on a multidomain model of the brain tissue and a homogenization argument for the diffusion processes. In our spatially distributed compartment model, communication between compartments occur both through local transport fluxes, as is the case within local astrocyte-neuron complexes, and through diffusion of some substances in some of the compartments. The model assumes that diffusion takes place in the extracellular space (ECS) and in the astrocyte compartment. In the astrocyte compartment, the diffusion across the syncytium network is implemented as a function of gap junction strength. The diffusion process is implemented numerically by means of a finite element method (FEM) based spatial discretization, and robust stiff solvers are used to time integrate the resulting large system. Computed experiments show the effects of ECS tortuosity, gap junction strength and spatial anisotropy in the astrocyte network on the brain energy metabolism.

Generalization of generative model for neuronal ensemble inference method.

Various brain functions that are necessary to maintain life activities materialize through the interaction of countless neurons. Therefore, it is important to analyze functional neuronal network. To elucidate the mechanism of brain function, many studies are being actively conducted on functional neuronal ensemble and hub, including all areas of neuroscience. In addition, recent study suggests that the existence of functional neuronal ensembles and hubs contributes to the efficiency of information processing. For these reasons, there is a demand for methods to infer functional neuronal ensembles from neuronal activity data, and methods based on Bayesian inference have been proposed. However, there is a problem in modeling the activity in Bayesian inference. The features of each neuron's activity have non-stationarity depending on physiological experimental conditions. As a result, the assumption of stationarity in Bayesian inference model impedes inference, which leads to destabilization of inference results and degradation of inference accuracy. In this study, we extend the range of the variable for expressing the neuronal state, and generalize the likelihood of the model for extended variables. By comparing with the previous study, our model can express the neuronal state in larger space. This generalization without restriction of the binary input enables us to perform soft clustering and apply the method to non-stationary neuroactivity data. In addition, for the effectiveness of the method, we apply the developed method to multiple synthetic fluorescence data generated from the electrical potential data in leaky integrated-and-fire model.

The Impact of Higher-Order Interactions on the Synchronization of Hindmarsh–Rose Neuron Maps under Different Coupling Functions

In network analysis, links depict the connections between each pair of network nodes. However, such pairwise connections fail to consider the interactions among more agents, which may be indirectly connected. Such non-pairwise or higher-order connections can be signified by involving simplicial complexes. The higher-order connections become even more noteworthy when it comes to neuronal network synchronization, an emerging phenomenon responsible for the many biological processes in real-world phenomena. However, involving higher-order interactions may considerably increase the computational costs. To confound this issue, map-based models are more suitable since they are faster, simpler, more flexible, and computationally more optimal. Therefore, this paper addresses the impact of pairwise and non-pairwise neuronal interactions on the synchronization state of 10 coupled memristive Hindmarsh–Rose neuron maps. To this aim, electrical, inner linking, and chemical synaptic functions are considered as two- and three-body interactions in three homogeneous and two heterogeneous cases. The results show that through chemical pairwise and non-pairwise synapses, the neurons achieve synchrony with the weakest coupling strengths.

Dissociation of vicarious and experienced rewards by coupling frequency within the same neural pathway

Vicarious reward, essential to social learning and decision making, is theorized to engage select brain regions similarly to experienced reward to generate a shared experience. However, it is just as important for neural systems to also differentiate vicarious from experienced rewards for social interaction. Here, we investigated the neuronal interaction between the primate anterior cingulate cortex gyrus (ACCg) and the basolateral amygdala (BLA) when social choices made by monkeys led to either vicarious or experienced reward. Coherence between ACCg spikes and BLA local field potential (LFP) selectively increased in gamma frequencies for vicarious reward, whereas it selectively increased in alpha/beta frequencies for experienced reward. These respectively enhanced couplings for vicarious and experienced rewards were uniquely observed following voluntary choices. Moreover, reward outcomes had consistently strong directional influences from ACCg to BLA. Our findings support a mechanism of vicarious reward where social agency is tagged by interareal coordination frequency within the same shared pathway.

The volatile anesthetic isoflurane differentially inhibits voltage-gated sodium channel currents between pyramidal and parvalbumin neurons in the prefrontal cortex.

How volatile anesthetics work remains poorly understood. Modulations of synaptic neurotransmission are the direct cellular mechanisms of volatile anesthetics in the central nervous system. Volatile anesthetics such as isoflurane may reduce neuronal interaction by differentially inhibiting neurotransmission between GABAergic and glutamatergic synapses. Presynaptic voltage-dependent sodium channels (Nav), which are strictly coupled with synaptic vesicle exocytosis, are inhibited by volatile anesthetics and may contribute to the selectivity of isoflurane between GABAergic and glutamatergic synapses. However, it is still unknown how isoflurane at clinical concentrations differentially modulates Nav currents between excitatory and inhibitory neurons at the tissue level. In this study, an electrophysiological recording was applied in cortex slices to investigate the effects of isoflurane on Nav between parvalbumin (PV+) and pyramidal neurons in PV-cre-tdTomato and/or vglut2-cre-tdTomato mice. Isoflurane at clinically relevant concentrations produced a hyperpolarizing shift in the voltage-dependent inactivation and slowed the recovery time from the fast inactivation in both cellular subtypes. Since the voltage of half-maximal inactivation was significantly depolarized in PV+ neurons compared to that of pyramidal neurons, isoflurane inhibited the peak Nav currents in pyramidal neurons more potently than those of PV+ neurons (35.95 ± 13.32% vs. 19.24 ± 16.04%, P = 0.036 by the Mann-Whitney test). Isoflurane differentially inhibits Nav currents between pyramidal and PV+ neurons in the prefrontal cortex, which may contribute to the preferential suppression of glutamate release over GABA release, resulting in the net depression of excitatory-inhibitory circuits in the prefrontal cortex.

Sudden bio-mathematical self-similarity and the uniqueness of human mass societies: from T-patterns and T-strings to T-societies.

With the explosive growth of human knowledge especially in the twenteeth century with even greater facilitation of access to knowledge, the world of even relatively recent great thinkers becomes daunting as seen from a modern viewpoint. Recently, humans ignored the existence of the complex intracellular world of cell organs, giant information molecules such as DNA, societies of specialized worker molecules (proteins), and generally the surprising nanoscale world visible to humanity since only a few decades ago. Moreover, computational power and video technology were inaccessible to all scientists from, for example, Aristotle to Freud, so new views and ideas seem to be expected about phenomena at all scales including nano and human. Some have arrived very recently. Thus urgently needed knowledge about the biology of animal and human behavior received the first Nobel Prize as late as 1973, in Physiology and Medicine, shared by Karl von Frisch, Konrad Lorenz, and Niko Tinbergen. Lorenz's Nobel lecture was entitled "Analogy as a Source of Knowledge" which did not mention self-analogy (self-similarity) as none of the species studied were part of others and knowledge of the nanoscale phenomena at the heart of this article had barely become available. The views and empirical findings presented in this article depend on such recent intracellular nanoscale insights and the development of a set of mathematical patterns, called T-system, of which only two are considered, the self-similar (i.e., parts having a structure similar to the whole) T-pattern and the derived T-string, a T-patterned material string (here, polymer or text). Specially developed algorithms implemented in the THEMETM software for T-pattern detection and analysis (TPA) allowed the detection of interaction T-patterns in humans, animals, and brain neuronal networks, showing self-similarity between animal interaction patterns and neuronal interaction patterns in their brains. TPA of DNA and text also showed unique self-similarity between modern human literate mass societies and the protein societies of their body cells, both with Giant Extra-Individual Purely Informational T-strings (GEIPIT; genomes or textomes) defining the behavioral potentials of their specialized citizens. This kind of society is here called T-society and only exists in humans and proteins, while the self-similarity between them only exists in human T-societies.

Developmental ethanol exposure has minimal impact on cerebellar microglial dynamics, morphology, and interactions with Purkinje cells during adolescence.

Fetal alcohol spectrum disorders (FASD) are the most common cause of non-heritable, preventable mental disability, occurring in almost 5% of births in the United States. FASD lead to physical, behavioral, and cognitive impairments, including deficits related to the cerebellum. There is no known cure for FASD and their mechanisms remain poorly understood. To better understand these mechanisms, we examined the cerebellum on a cellular level by studying microglia, the principal immune cells of the central nervous system, and Purkinje cells, the sole output of the cerebellum. Both cell types have been shown to be affected in models of FASD, with increased cell death, immune activation of microglia, and altered firing in Purkinje cells. While ethanol administered in adulthood can acutely depress the dynamics of the microglial process arbor, it is unknown how developmental ethanol exposure impacts microglia dynamics and their interactions with Purkinje cells in the long term. To address this question, we used a mouse model of human 3rd trimester exposure, whereby L7cre/Ai9+/-/Cx3cr1G/+ mice (with fluorescently labeled microglia and Purkinje cells) of both sexes were subcutaneously treated with a binge-level dose of ethanol (5.0 g/kg/day) or saline from postnatal days 4-9. Cranial windows were implanted in adolescent mice above the cerebellum to examine the long-term effects of developmental ethanol exposure on cerebellar microglia and Purkinje cell interactions using in vivo two-photon imaging. We found that cerebellar microglia dynamics and morphology were not affected after developmental ethanol exposure. Microglia dynamics were also largely unaltered with respect to how they interact with Purkinje cells, although subtle changes in these interactions were observed in females in the molecular layer of the cerebellum. This work suggests that there are limited in vivo long-term effects of ethanol exposure on microglia morphology, dynamics, and neuronal interactions, so other avenues of research may be important in elucidating the mechanisms of FASD.

Spatial Attention Modulates Neuronal Interactions between Simple and Complex Cells in V1.

Visual perception is profoundly modulated by spatial attention, which can selectively prioritize goal-related information. Previous studies found spatial attention facilitated the efficacy of neuronal communication between visual cortices with hierarchical organizations. In the primary visual cortex (V1), there is also a hierarchical connection between simple (S) and complex (C) cells. We wonder whether and how spatial attention modulates neuronal communication within V1, especially for neuronal pairs with heterogeneous visual input. We simultaneously recorded the pairs' activity from macaque monkeys when they performed a spatial-attention-involved task, then applied likelihood-based Granger causality analysis to explore attentional modulation of neuronal interactions. First, a significant attention-related decrease in Granger causality was found in S-C pairs, which primarily displayed in the S-to-C feedforward connection. Second, the interaction strength of the feedforward connection was significantly higher than that of the feedback under attend toward (AT) conditions. Although information flow did not alter as the attentional focus shifted, the strength of communications between target- and distractor-stimuli-covered neurons differed only when attending to complex cells' receptive fields (RFs). Furthermore, pairs' communications depended on the attentional modulation of neurons' firing rates. Our findings demonstrate spatial attention does not induce specific information flow but rather amplifies directed communication within V1.

Approximating the Effect of Consciousness on Stochastic Brain Structures

There is a large amount of evidence in the Parapsychology literature that indicates thatconsciousness is not an emergent property of neuronal interactions and can exist andfunction independently of a brain. Here we examine mathematical methods that canbe used to derive dynamic equations for the mind-matter interactions occurring in thebrain that these observations imply the existence of. We use the moments method toapproximate the effect that consciousness has on stochastic binary decision-makingneural networks , which we model using biologically realistic Wilson-Cowan equations(Deco et al., 2007). We show that small changes in the variance of the randomness (onthe order of 0.1 Hz2) consumed by the neural networks can bias the networks to selectone binary decision value over the other. Using observations about the interconnectednessof relatively isolated groups of neurons, we argue that biases of the size predictedby the approximation would be sufficient to allow a brain-independent consciousnessto exert significant control over the brain. The results that we present here are relevantto any theory positing that rote computations carried out by neurons are not the solecontributor to consciousness.

Neuronal cells co-ordinate myeloid-epithelial cell interaction to regulate intestinal inflammation

Abstract Epithelial response to injury is coordinated through an intricate interaction with neuronal and myeloid cells, however the signaling modules involved are not well understood. In humans, somatic mutations in Tet methylcytosine dioxygenase 2 (TET2), a DNA demethylase, are commonly observed during ageing in myeloid cells and known to modulate inflammatory responses. Using a mouse model that lacks TET2 in myeloid cells (Tet2 ΔLysM), we show that myeloid cells and sympathetic neurons form a signaling nexus that controls differentiation of enterochromaffin cells and serotonin production during colonic inflammation. Under physiological conditions, TET2 restricts IL-1β production by myeloid cells which in turn controls the intestinal sympathetic architecture. During inflammation, IL1R signaling limits sympathetic cues that drive differentiation of enterochromaffin cells through α1-adrenergic signaling. As a result, enterochromaffin differentiation and colitis progression in response to mucosal injury is attenuated in Tet2 ΔLysMmice. Further, protection from colitis in Tet2 ΔLysMmice is mediated by its catalytic activity, and dependent on sympathetic neurons and IL1R signaling. Adrenergic control of epithelial response and pro-colitic serotonin production is also evident under conditions of physiological stress that leads to increased colitis susceptibility. Overall, our study reveals a sympathetic-epithelial axis that controls the severity of colitis and is modulated by myeloid-derived IL-1β and physiological stress. Our findings may also explain why inflammatory bowel disease in the elderly, where TET2 mutations in myeloid cells are common, is less severe and suggests TET2 activity as an attractive target for IBD. Supported by the US National Institutes of Health (DK067180) to B.J, the University of Chicago's Center for Interdisciplinary Study of Inflammatory Intestinal Disorders (C-IID) Pilot & Feasibility Award (NIDDK P30 DK042086) to A.M. and D.S, Crohn’s and Colitis Foundation Career Development Award #964209 to A.M. and G.I. Research Foundation Associates Board Award to A.M. and D.S.

Interaction of the tau fibrils with the neuronal membrane

Tau proteins are recently gaining a lot of interest due to their active role in causing a range of tauopathies. Molecular mechanisms underlying the tau interaction with the neuronal membrane are hitherto unknown and difficult to characterize using experimental methods. Using the cryo-EM structure of the tau-fibrils we have used atomistic molecular dynamics simulation to model the tau fibril and neuronal membrane interaction using explicit solvation. The dynamics and structural characteristics of the tau fibril with the neuronal membrane are compared to the tau fibril in the aqueous phase to corroborate the effect of the neuronal membrane in the tau structure. Tau fibrils have been modelled using CHARMM-36m force field and the six component neuronal membrane composition is taken from the earlier simulation results. The timescale conceivable in our molecular dynamics simulations is of the order of microseconds which captures the onset of the interaction of the tau fibrils with the neuronal membrane. This interaction is found to impact the tau pathogenesis that finally causes neuronal toxicity. Our study initiates the understanding of tau conformational ensemble in the presence of neuronal membrane and sheds the light on the significant tau-membrane interactions.

Endocannabinoid-dependent decrease of GABAergic transmission on dopaminergic neurons is associated with susceptibility to cocaine stimulant effects in pre-adolescent male MAOA hypomorphic mice exposed to early life stress

Vulnerability to cocaine use disorder depends upon a combination of genetic and environmental risk factors. While early life adversity is a critical environmental vulnerability factor for drug misuse, allelic variants of the monoamine oxidase A (MAOA) gene have been shown to moderate its influence on the risk of drug-related problems. However, data on the interactions between MAOA variants and early life stress (ES) with respect to predisposition to cocaine abuse are limited. Here, we show that a mouse model capturing the interaction of genetic (low-activity alleles of the Maoa gene; MAOANeo) and environmental (i.e., ES) vulnerability factors displays an increased sensitivity to repeated in vivo cocaine psychomotor stimulant actions associated with a reduction of GABAA receptor-mediated inhibition of dopamine neurons of the ventral tegmental area (VTA). Depolarization-induced suppression of inhibition (DSI), a 2-arachidonoylglycerol (2AG)-dependent form of short-term plasticity, also becomes readily expressed by dopamine neurons from male MAOANeo ES mice repeatedly treated with cocaine. The activation of either dopamine D2 or CB1 receptors contributes to cocaine-induced DSI expression, decreased GABA synaptic efficacy, and hyperlocomotion. Next, in vivo pharmacological enhancement of 2AG signaling during repeated cocaine exposure occludes its actions both in vivo and ex vivo. This data extends our knowledge of the multifaceted sequelae imposed by this gene-environment interaction in VTA dopamine neurons of male pre-adolescent mice and contributes to our understanding of neural mechanisms of vulnerability for early onset cocaine use.

As without, so within: how the brain's temporo-spatial alignment to the environment shapes consciousness.

Consciousness is constituted by a structure that includes contents as foreground and the environment as background. This structural relation between the experiential foreground and background presupposes a relationship between the brain and the environment, often neglected in theories of consciousness. The temporo-spatial theory of consciousness addresses the brain-environment relation by a concept labelled 'temporo-spatial alignment'. Briefly, temporo-spatial alignment refers to the brain's neuronal activity's interaction with and adaption to interoceptive bodily and exteroceptive environmental stimuli, including their symmetry as key for consciousness. Combining theory and empirical data, this article attempts to demonstrate the yet unclear neuro-phenomenal mechanisms of temporo-spatial alignment. First, we suggest three neuronal layers of the brain's temporo-spatial alignment to the environment. These neuronal layers span across a continuum from longer to shorter timescales. (i) The background layer comprises longer and more powerful timescales mediating topographic-dynamic similarities between different subjects' brains. (ii) The intermediate layer includes a mixture of medium-scaled timescales allowing for stochastic matching between environmental inputs and neuronal activity through the brain's intrinsic neuronal timescales and temporal receptive windows. (iii) The foreground layer comprises shorter and less powerful timescales for neuronal entrainment of stimuli temporal onset through neuronal phase shifting and resetting. Second, we elaborate on how the three neuronal layers of temporo-spatial alignment correspond to their respective phenomenal layers of consciousness. (i) The inter-subjectively shared contextual background of consciousness. (ii) An intermediate layer that mediates the relationship between different contents of consciousness. (iii) A foreground layer that includes specific fast-changing contents of consciousness. Overall, temporo-spatial alignment may provide a mechanism whose different neuronal layers modulate corresponding phenomenal layers of consciousness. Temporo-spatial alignment can provide a bridging principle for linking physical-energetic (free energy), dynamic (symmetry), neuronal (three layers of distinct time-space scales) and phenomenal (form featured by background-intermediate-foreground) mechanisms of consciousness.

A tribute to Leif Hertz: The historical context of his pioneering studies of the roles of astrocytes in brain energy metabolism, neurotransmission, cognitive functions, and pharmacology identifies important, unresolved topics for future studies.

Leif Hertz, M.D., D.Sc. (honōris causā) (1930-2018), was one of the original and noteworthy participants in the International Conference on Brain Energy Metabolism (ICBEM) series since its inception in 1993. The biennial ICBEM conferences are organized by neuroscientists interested in energetics and metabolism underlying neural functions; they have had a high impact on conceptual and experimental advances in these fields and on promoting collaborative interactions among neuroscientists. Leif made major contributions to ICBEM discussions and understanding of metabolic and signaling characteristics of astrocytes and their roles in brain function. His studies ranged from uptake of K+ from extracellular fluid and its stimulation of astrocytic respiration, identification, and regulation of enzymes specifically or preferentially expressed in astrocytes in the glutamate-glutamine cycle of excitatory neurotransmission, a requirement for astrocytic glycogenolysis for fueling K+ uptake, involvement of glycogen in memory consolidation in the chick, and pharmacology of astrocytes. This tribute to Leif Hertz highlights his major discoveries, the high impact of his work on astrocyte-neuron interactions, and his unparalleled influence on understanding the cellular basis of brain energy metabolism. His work over six decades has helped integrate the roles of astrocytes into neurotransmission where oxidative and glycogenolytic metabolism during neurotransmitter glutamate turnover are key aspects of astrocytic energetics. Leif recognized that brain astrocytic metabolism is greatly underestimated unless the volume fraction of astrocytes is taken into account. Adjustment for pathway rates expressed per gram tissue for volume fraction indicates that astrocytes have much higher oxidative rates than neurons and astrocytic glycogen concentrations and glycogenolytic rates during sensory stimulation in vivo are similar to those in resting and exercising muscle, respectively. These novel insights are typical of Leif's astute contributions to the energy metabolism field, and his publications have identified unresolved topics that provide the neuroscience community with challenges and opportunities for future research.

Abstract 3630: TrkA+ sensory neurons modulate macrophage phenotype in osteosarcoma

Abstract Introduction: Osteosarcoma (OS) is the most common primary malignancy of the skeleton, and inordinately affects young adults. Despite improved outcomes with current multimodal care, the prognosis for patients with metastatic disease is grim. Peripheral neural regulation of cancer growth has long been suggested by clinical observations in pancreatic and prostate cancers. Prior reports suggest peripheral nerve sprouting in osteosarcoma, but the functional roles of sensory nerves in osteosarcoma are unknown. Here, the role of TrkA+ sensory nerves in OS disease progression was assayed. Methods: All experiments were conducted under IACUC approval at Johns Hopkins University. TrkAF592A mice which are homozygous for a phenylalanine-to-alanine point mutation in exon 12 of Ntrk1 gene were crossbred with NOD scid mice (TrkAF592A/Scid). TrkA inhibition was performed by 1NMPP1 treatment. In vivo tumor growth was examined using a periosteal xenograft model. 1 million human 143B-luc OS cells were injected. Analysis was performed using serial measurements of tumor size and IVIS imaging. Nerve distribution and macrophage polarization within the tumor microenvironment was documented using immunostaining for Beta III Tubulin (TUBB3), CD86, CD206 and F4/80. Results: Inhibition of TrkA led to a significant reduction in Tubb3+ nerves (88.4%) within and around the OS xenografts. In addition, tumors within TrkAF592A/Scid animals demonstrated slower growth, including a 51.5% reduction in tumor size and 60.0% reduction in IVIS luciferase activity at 4 wks. Histologic examination showed a reduction in macrophage infiltration and reprogramming of macrophages from an M2-like to M1-like phenotype in tumors with chemical denervation. Remarkably, this was associated with a reduction in Ki67 proliferative index (80.1%) and CD31 immunofluorescent staining (60.8%) within the tumors. Overall survival of mice with TrkA inhibition was significantly prolonged (p=0.0003). Retrograde tracing identified the sensory nerve fibers innervating the periosteum originated from L3-L5 lumbar DRGs and RNA seq identified OS-derived neurotrophins and axon guidance molecules. Discussion: Disruption of TrkA+ nerves significantly mitigates OS disease progression in a mouse xenograft model, including a significant improved overall survival. These findings are associated with a reduction of macrophage infiltration and macrophage re-polarization. Ongoing studies are examining the molecular mechanisms that mediate nerve-to-macrophage interaction in peripheral nerves and DRG neurons using a combination of sequencing approaches. Significance/Clinical Relevance: Sensory neurons positively regulate osteosarcoma growth and disease progression. Use of chemical or microsurgical approaches to denervate tumors may represent a future adjunctive therapy to both improve pain and prognosis in high grade bone sarcomas. Citation Format: Qizhi Qin, Sowmya Ramesh Ramesh, Thomas L. Clemens, Aaron W. James. TrkA+ sensory neurons modulate macrophage phenotype in osteosarcoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3630.

Multi-band oscillations emerge from a simple spiking network.

In the brain, coherent neuronal activities often appear simultaneously in multiple frequency bands, e.g., as combinations of alpha (8-12 Hz), beta (12.5-30 Hz), and gamma (30-120 Hz) oscillations, among others. These rhythms are believed to underlie information processing and cognitive functions and have been subjected to intense experimental and theoretical scrutiny. Computational modeling has provided a framework for the emergence of network-level oscillatory behavior from the interaction of spiking neurons. However, due to the strong nonlinear interactions between highly recurrent spiking populations, the interplay between cortical rhythms in multiple frequency bands has rarely been theoretically investigated. Many studies invoke multiple physiological timescales (e.g., various ion channels or multiple types of inhibitory neurons) or oscillatory inputs to produce rhythms in multi-bands. Here, we demonstrate the emergence of multi-band oscillations in a simple network consisting of one excitatory and one inhibitory neuronal population driven by constant input. First, we construct a data-driven, Poincaré section theory for robust numerical observations of single-frequency oscillations bifurcating into multiple bands. Then, we develop model reductions of the stochastic, nonlinear, high-dimensional neuronal network to capture the appearance of multi-band dynamics and the underlying bifurcations theoretically. Furthermore, when viewed within the reduced state space, our analysis reveals conserved geometrical features of the bifurcations on low-dimensional dynamical manifolds. These results suggest a simple geometric mechanism behind the emergence of multi-band oscillations without appealing to oscillatory inputs or multiple synaptic or neuronal timescales. Thus, our work points to unexplored regimes of stochastic competition between excitation and inhibition behind the generation of dynamic, patterned neuronal activities.