Lateral flexion of a compliant spine improves motor performance in a bioinspired mouse robot.

A flexible spine is critical to the motion capability of most animals and plays a pivotal role in their agility. Although state-of-the-art legged robots have already achieved very dynamic and agile movement solely relying on their legs, they still exhibit the type of stiff movement that compromises movement efficiency. The integration of a flexible spine thus appears to be a promising approach to improve their agility, especially for small and underactuated quadruped robots that are underpowered because of size limitations. Here, we show that the lateral flexion of a compliant spine can promote both walking speed and maneuver agility for a neurorobotic mouse (NeRmo). We present NeRmo as a biomimetic robotic mouse that mimics the morphology of biological mice and their muscle-tendon actuation system. First, by leveraging the lateral flexion of the compliant spine, NeRmo can greatly increase its static stability in an initially unstable configuration by adjusting its posture. Second, the lateral flexion of the spine can also effectively extend the stride length of a gait and therefore improve the walking speeds of NeRmo. Finally, NeRmo shows agile maneuvers that require both a small turning radius and fast walking speed with the help of the spine. These results advance our understanding of spine-based quadruped locomotion skills and highlight promising design concepts to develop more agile legged robots.

Embodied bidirectional simulation of a spiking cortico-basal ganglia-cerebellar-thalamic brain model and a mouse musculoskeletal body model distributed across computers including the supercomputer Fugaku.

Embodied simulation with a digital brain model and a realistic musculoskeletal body model provides a means to understand animal behavior and behavioral change. Such simulation can be too large and complex to conduct on a single computer, and so distributed simulation across multiple computers over the Internet is necessary. In this study, we report our joint effort on developing a spiking brain model and a mouse body model, connecting over the Internet, and conducting bidirectional simulation while synchronizing them. Specifically, the brain model consisted of multiple regions including secondary motor cortex, primary motor and somatosensory cortices, basal ganglia, cerebellum and thalamus, whereas the mouse body model, provided by the Neurorobotics Platform of the Human Brain Project, had a movable forelimb with three joints and six antagonistic muscles to act in a virtual environment. Those were simulated in a distributed manner across multiple computers including the supercomputer Fugaku, which is the flagship supercomputer in Japan, while communicating via Robot Operating System (ROS). To incorporate models written in C/C++ in the distributed simulation, we developed a C++ version of the rosbridge library from scratch, which has been released under an open source license. These results provide necessary tools for distributed embodied simulation, and demonstrate its possibility and usefulness toward understanding animal behavior and behavioral change.

Meta-Reinforcement Learning in Nonstationary and Nonparametric Environments.

Recent state-of-the-art artificial agents lack the ability to adapt rapidly to new tasks, as they are trained exclusively for specific objectives and require massive amounts of interaction to learn new skills. Meta-reinforcement learning (meta-RL) addresses this challenge by leveraging knowledge learned from training tasks to perform well in previously unseen tasks. However, current meta-RL approaches limit themselves to narrow parametric and stationary task distributions, ignoring qualitative differences and nonstationary changes between tasks that occur in the real world. In this article, we introduce a Task-Inference-based meta-RL algorithm using explicitly parameterized Gaussian variational autoencoders (VAEs) and gated Recurrent units (TIGR), designed for nonparametric and nonstationary environments. We employ a generative model involving a VAE to capture the multimodality of the tasks. We decouple the policy training from the task-inference learning and efficiently train the inference mechanism on the basis of an unsupervised reconstruction objective. We establish a zero-shot adaptation procedure to enable the agent to adapt to nonstationary task changes. We provide a benchmark with qualitatively distinct tasks based on the half-cheetah environment and demonstrate the superior performance of TIGR compared with state-of-the-art meta-RL approaches in terms of sample efficiency (three to ten times faster), asymptotic performance, and applicability in nonparametric and nonstationary environments with zero-shot adaptation. Videos can be viewed at https://videoviewsite.wixsite.com/tigr.

Challenges in glioblastoma research: focus on the tumor microenvironment.

Glioblastoma (GBM) is the most deadly type of malignant brain tumor, despite extensive molecular analyses of GBM cells. In recent years, the tumor microenvironment (TME) has been recognized as an important player and therapeutic target in GBM. However, there is a need for a full and integrated understanding of the different cellular and molecular components involved in the GBM TME and their interactions for the development of more efficient therapies. In this review, we provide a comprehensive report of the GBM TME, which assembles the contributions of physicians and translational researchers working on brain tumor pathology and therapy in France. We propose a holistic view of the subject by delineating the specific features of the GBM TME at the cellular, molecular, and therapeutic levels.

Robotic Manipulation in Dynamic Scenarios via Bounding-Box-Based Hindsight Goal Generation.

By relabeling past experience with heuristic or curriculum goals, state-of-the-art reinforcement learning (RL) algorithms such as hindsight experience replay (HER), hindsight goal generation (HGG), and graph-based HGG (G-HGG) have been able to solve challenging robotic manipulation tasks in multigoal settings with sparse rewards. HGG outperforms HER in challenging tasks in which goals are difficult to explore by learning from a curriculum, in which intermediate goals are selected based on the Euclidean distance to target goals. G-HGG enhances HGG by selecting intermediate goals from a precomputed graph representation of the environment, which enables its applicability in an environment with stationary obstacles. However, G-HGG is not applicable to manipulation tasks with dynamic obstacles, since its graph representation is only valid in static scenarios and fails to provide any correct information to guide the exploration. In this article, we propose bounding-box-based HGG (Bbox-HGG), an extension of G-HGG selecting hindsight goals with the help of image observations of the environment, which makes it applicable to tasks with dynamic obstacles. We evaluate Bbox-HGG on four challenging manipulation tasks, where significant enhancements in both sample efficiency and overall success rate are shown over state-of-the-art algorithms. The videos can be viewed at https://videoviewsite.wixsite.com/bbhgg.

Deploying and Optimizing Embodied Simulations of Large-Scale Spiking Neural Networks on HPC Infrastructure.

Simulating the brain-body-environment trinity in closed loop is an attractive proposal to investigate how perception, motor activity and interactions with the environment shape brain activity, and vice versa. The relevance of this embodied approach, however, hinges entirely on the modeled complexity of the various simulated phenomena. In this article, we introduce a software framework that is capable of simulating large-scale, biologically realistic networks of spiking neurons embodied in a biomechanically accurate musculoskeletal system that interacts with a physically realistic virtual environment. We deploy this framework on the high performance computing resources of the EBRAINS research infrastructure and we investigate the scaling performance by distributing computation across an increasing number of interconnected compute nodes. Our architecture is based on requested compute nodes as well as persistent virtual machines; this provides a high-performance simulation environment that is accessible to multi-domain users without expert knowledge, with a view to enable users to instantiate and control simulations at custom scale via a web-based graphical user interface. Our simulation environment, entirely open source, is based on the Neurorobotics Platform developed in the context of the Human Brain Project, and the NEST simulator. We characterize the capabilities of our parallelized architecture for large-scale embodied brain simulations through two benchmark experiments, by investigating the effects of scaling compute resources on performance defined in terms of experiment runtime, brain instantiation and simulation time. The first benchmark is based on a large-scale balanced network, while the second one is a multi-region embodied brain simulation consisting of more than a million neurons and a billion synapses. Both benchmarks clearly show how scaling compute resources improves the aforementioned performance metrics in a near-linear fashion. The second benchmark in particular is indicative of both the potential and limitations of a highly distributed simulation in terms of a trade-off between computation speed and resource cost. Our simulation architecture is being prepared to be accessible for everyone as an EBRAINS service, thereby offering a community-wide tool with a unique workflow that should provide momentum to the investigation of closed-loop embodiment within the computational neuroscience community.

The Neurorobotics Platform Robot Designer: Modeling Morphologies for Embodied Learning Experiments.

The more we investigate the principles of motion learning in biological systems, the more we reveal the central role that body morphology plays in motion execution. Not only does anatomy define the kinematics and therefore the complexity of possible movements, but it now becomes clear that part of the computation required for motion control is offloaded to body dynamics (a phenomenon referred to as "Morphological Computation.") Consequentially, a proper design of body morphology is essential to carry out meaningful simulations on motor control of robotic and musculoskeletal systems. The design should not be fixed for simulation experiments beforehand, but is a central research aspect in every motion learning experiment that requires continuous adaptation during the experimental phase. We herein introduce a plugin for the 3D modeling suite Blender that enables researchers to design morphologies for simulation experiments in, particularly but not restricted to, the Neurorobotics Platform. We include design capabilities for both musculoskeletal bodies, as well as robotic systems in the Robot Designer. Thereby, we hope to not only foster understanding of biological motions and enabling better robot designs, but enabling true Neurorobotic experiments that may consist of biomimetic models such as tendon-driven robot as a mix of both or a transition between both biology and technology. This plugin helps researchers design and parameterize models with a Graphical User Interface and thus simplifies and speeds up the overall design process.

Chemotactic cell migration: the core autophagy protein ATG9A is at the leading edge.

Accumulating data indicate that several components of the macroautophagy/autophagy machinery mediate additional functions, which do not depend on autophagosome biogenesis or lysosomal cargo degradation. In this context, we found that the core autophagy protein ATG9A participates in the chemotactic movement of several cell lines, including highly invasive glioblastoma cells. Accordingly, ATG9A-depleted cells are unable to form large and persistent leading-edge protrusions. By the design of an ATG9A-pHluorin construct and TIRF imaging, we established that ATG9A-positive vesicles are targeted toward the migration front, where their exocytosis is synchronized with protrusive activity. We finally demonstrated that ATG9A, through its interaction with clathrin adaptor complexes, controls the delivery of ITGB1 (integrin subunit beta 1) to the migration front and normal adhesion dynamics. Together, our work indicates that ATG9A protein has a wider role than anticipated and constitutes a critical component of vesicular trafficking allowing the expansion of cell protrusions and their anchorage to the extracellular matrix.

The core autophagy protein ATG9A controls dynamics of cell protrusions and directed migration.

Chemotactic migration is a fundamental cellular behavior relying on the coordinated flux of lipids and cargo proteins toward the leading edge. We found here that the core autophagy protein ATG9A plays a critical role in the chemotactic migration of several human cell lines, including highly invasive glioma cells. Depletion of ATG9A protein altered the formation of large and persistent filamentous actin (F-actin)-rich lamellipodia that normally drive directional migration. Using live-cell TIRF microscopy, we demonstrated that ATG9A-positive vesicles are targeted toward the migration front of polarized cells, where their exocytosis correlates with protrusive activity. Finally, we found that ATG9A was critical for efficient delivery of ß1 integrin to the leading edge and normal adhesion dynamics. Collectively, our data uncover a new function for ATG9A protein and indicate that ATG9A-positive vesicles are mobilized during chemotactic stimulation to facilitate expansion of the lamellipodium and its anchorage to the extracellular matrix.

Complex Robotic Manipulation via Graph-Based Hindsight Goal Generation.

Reinforcement learning algorithms, such as hindsight experience replay (HER) and hindsight goal generation (HGG), have been able to solve challenging robotic manipulation tasks in multigoal settings with sparse rewards. HER achieves its training success through hindsight replays of past experience with heuristic goals but underperforms in challenging tasks in which goals are difficult to explore. HGG enhances HER by selecting intermediate goals that are easy to achieve in the short term and promising to lead to target goals in the long term. This guided exploration makes HGG applicable to tasks in which target goals are far away from the object's initial position. However, the vanilla HGG is not applicable to manipulation tasks with obstacles because the Euclidean metric used for HGG is not an accurate distance metric in such an environment. Although, with the guidance of a handcrafted distance grid, grid-based HGG can solve manipulation tasks with obstacles, a more feasible method that can solve such tasks automatically is still in demand. In this article, we propose graph-based hindsight goal generation (G-HGG), an extension of HGG selecting hindsight goals based on shortest distances in an obstacle-avoiding graph, which is a discrete representation of the environment. We evaluated G-HGG on four challenging manipulation tasks with obstacles, where significant enhancements in both sample efficiency and overall success rate are shown over HGG and HER. Videos can be viewed at https://videoviewsite.wixsite.com/ghgg.

Toward Cognitive Navigation: Design and Implementation of a Biologically Inspired Head Direction Cell Network.

As a vital cognitive function of animals, the navigation skill is first built on the accurate perception of the directional heading in the environment. Head direction cells (HDCs), found in the limbic system of animals, are proven to play an important role in identifying the directional heading allocentrically in the horizontal plane, independent of the animal's location and the ambient conditions of the environment. However, practical HDC models that can be implemented in robotic applications are rarely investigated, especially those that are biologically plausible and yet applicable to the real world. In this article, we propose a computational HDC network that is consistent with several neurophysiological findings concerning biological HDCs and then implement it in robotic navigation tasks. The HDC network keeps a representation of the directional heading only relying on the angular velocity as an input. We examine the proposed HDC model in extensive simulations and real-world experiments and demonstrate its excellent performance in terms of accuracy and real-time capability.

Targeting the Urotensin II/UT G Protein-Coupled Receptor to Counteract Angiogenesis and Mesenchymal Hypoxia/Necrosis in Glioblastoma.

Glioblastomas (GBMs) are the most common primary brain tumors characterized by strong invasiveness and angiogenesis. GBM cells and microenvironment secrete angiogenic factors and also express chemoattractant G protein-coupled receptors (GPCRs) to their advantage. We investigated the role of the vasoactive peptide urotensin II (UII) and its receptor UT on GBM angiogenesis and tested potential ligand/therapeutic options based on this system. On glioma patient samples, the expression of UII and UT increased with the grade with marked expression in the vascular and peri-necrotic mesenchymal hypoxic areas being correlated with vascular density. In vitro human UII stimulated human endothelial HUV-EC-C and hCMEC/D3 cell motility and tubulogenesis. In mouse-transplanted Matrigel sponges, mouse (mUII) and human UII markedly stimulated invasion by macrophages, endothelial, and smooth muscle cells. In U87 GBM xenografts expressing UII and UT in the glial and vascular compartments, UII accelerated tumor development, favored hypoxia and necrosis associated with increased proliferation (Ki67), and induced metalloproteinase (MMP)-2 and -9 expression in Nude mice. UII also promoted a "tortuous" vascular collagen-IV expressing network and integrin expression mainly in the vascular compartment. GBM angiogenesis and integrin αvß3 were confirmed by in vivo 99mTc-RGD tracer imaging and tumoral capture in the non-necrotic area of U87 xenografts in Nude mice. Peptide analogs of UII and UT antagonist were also tested as potential tumor repressor. Urotensin II-related peptide URP inhibited angiogenesis in vitro and failed to attract vascular and inflammatory components in Matrigel in vivo. Interestingly, the UT antagonist/biased ligand urantide and the non-peptide UT antagonist palosuran prevented UII-induced tubulogenesis in vitro and significantly delayed tumor growth in vivo. Urantide drastically prevented endogenous and UII-induced GBM angiogenesis, MMP, and integrin activations, associated with GBM tumoral growth. These findings show that UII induces GBM aggressiveness with necrosis and angiogenesis through integrin activation, a mesenchymal behavior that can be targeted by UT biased ligands/antagonists.

Ethical and Social Aspects of Neurorobotics.

The interdisciplinary field of neurorobotics looks to neuroscience to overcome the limitations of modern robotics technology, to robotics to advance our understanding of the neural system's inner workings, and to information technology to develop tools that support those complementary endeavours. The development of these technologies is still at an early stage, which makes them an ideal candidate for proactive and anticipatory ethical reflection. This article explains the current state of neurorobotics development within the Human Brain Project, originating from a close collaboration between the scientific and technical experts who drive neurorobotics innovation, and the humanities and social sciences scholars who provide contextualising and reflective capabilities. This article discusses some of the ethical issues which can reasonably be expected. On this basis, the article explores possible gaps identified within this collaborative, ethical reflection that calls for attention to ensure that the development of neurorobotics is ethically sound and socially acceptable and desirable.

Glial Endozepines Reverse High-Fat Diet-Induced Obesity by Enhancing Hypothalamic Response to Peripheral Leptin.

Research on energy homeostasis has focused on neuronal signaling; however, the role of glial cells has remained little explored. Glial endozepines exert anorexigenic actions by mechanisms which remain poorly understood. In this context, the present study was designed to decipher the mechanisms underlying the anorexigenic action of endozepines and to investigate their potential curative effect on high-fat diet-induced obesity. We carried out a combination of physiological, pharmacological, and molecular analyses together to dissect the underlying mechanisms of endozepine-induced hypophagia. To evaluate the potential anti-obesity effect of endozepines, different model of obesity were used, i.e., ob/ob and diet-induced obese mice. We show that the intracerebral administration of endozepines enhances satiety by targeting anorexigenic brain circuitry and induces STAT3 phosphorylation, a hallmark of leptin signaling. Strikingly, endozepines are entirely ineffective at reducing food intake in the presence of a circulating leptin antagonist and in leptin-deficient mice (ob/ob) but potentiate the reduced food intake and weight loss induced by exogenous leptin administration in these animals. Endozepines reversed high fat diet-induced obesity by reducing food intake and restored leptin-induced STAT3 phosphorylation in the hypothalamus. Interestingly, we observed that glucose and insulin synergistically enhance tanycytic endozepine expression and release. Finally, endozepines, which induce ERK activation necessary for leptin transport into the brain in cultured tanycytes, require tanycytic leptin receptor expression to promote STAT3 phosphorylation in the hypothalamus. Our data identify endozepines as potential anti-obesity compounds in part through the modulation of the LepR-ERK-dependent tanycytic leptin shuttle.

Development of Novel 111-In-Labelled DOTA Urotensin II Analogues for Targeting the UT Receptor Overexpressed in Solid Tumours.

Overexpression of G protein-coupled receptors (GPCRs) in tumours is widely used to develop GPCR-targeting radioligands for solid tumour imaging in the context of diagnosis and even treatment. The human vasoactive neuropeptide urotensin II (hUII), which shares structural analogies with somatostatin, interacts with a single high affinity GPCR named UT. High expression of UT has been reported in several types of human solid tumours from lung, gut, prostate, or breast, suggesting that UT is a valuable novel target to design radiolabelled hUII analogues for cancer diagnosis. In this study, two original urotensinergic analogues were first conjugated to a DOTA chelator via an aminohexanoic acid (Ahx) hydrocarbon linker and then -hUII and DOTA-urantide, complexed to the radioactive metal indium isotope to successfully lead to radiolabelled DOTA-Ahx-hUII and DOTA-Ahx-urantide. The 111In-DOTA-hUII in human plasma revealed that only 30% of the radioligand was degraded after a 3-h period. DOTA-hUII and DOTA-urantide exhibited similar binding affinities as native peptides and relayed calcium mobilization in HEK293 cells expressing recombinant human UT. DOTA-hUII, not DOTA-urantide, was able to promote UT internalization in UT-expressing HEK293 cells, thus indicating that radiolabelled 111In-DOTA-hUII would allow sufficient retention of radioactivity within tumour cells or radiolabelled DOTA-urantide may lead to a persistent binding on UT at the plasma membrane. The potential of these radioligands as candidates to target UT was investigated in adenocarcinoma. We showed that hUII stimulated the migration and proliferation of both human lung A549 and colorectal DLD-1 adenocarcinoma cell lines endogenously expressing UT. In vivo intravenous injection of 111In-DOTA-hUII in C57BL/6 mice revealed modest organ signals, with important retention in kidney. 111In-DOTA-hUII or 111In-DOTA-urantide were also injected in nude mice bearing heterotopic xenografts of lung A549 cells or colorectal DLD-1 cells both expressing UT. The observed significant renal uptake and low tumour/muscle ratio (around 2.5) suggest fast tracer clearance from the organism. Together, DOTA-hUII and DOTA-urantide were successfully radiolabelled with 111Indium, the first one functioning as a UT agonist and the second one as a UT-biased ligand/antagonist. To allow tumour-specific targeting and prolong body distribution in preclinical models bearing some solid tumours, these radiolabelled urotensinergic analogues should be optimized for being used as potential molecular tools for diagnosis imaging or even treatment tools.

Endozepines and their receptors: Structure, functions and pathophysiological significance.

The existence of specific binding sites for benzodiazepines (BZs) in the brain has prompted the search for endogenous BZ receptor ligands designated by the generic term « endozepines ¼. This has led to the identification of an 86-amino acid polypeptide capable of displacing [3H]diazepam binding to brain membranes, thus called diazepam-binding inhibitor (DBI). It was subsequently found that the sequence of DBI is identical to that of a lipid carrier protein termed acyl-CoA-binding protein (ACBP). The primary structure of DBI/ACBP has been well preserved, suggesting that endozepines exert vital functions. The DBI/ACBP gene is expressed by astroglial cells in the central nervous system, and by various cell types in peripheral organs. Endoproteolytic cleavage of DBI/ACBP generates several bioactive peptides including a triakontatetraneuropeptide that acts as a selective ligand of peripheral BZ receptors/translocator protein, and an octadecaneuropeptide that activates a G protein-coupled receptor and behaves as an allosteric modulator of the GABAAR. Although DBI/ACBP is devoid of a signal peptide, endozepines are released by astrocytes in a regulated manner. Consistent with the diversity and wide distribution of BZ-binding sites, endozepines appear to exert a large array of biological functions and pharmacological effects. Thus, intracerebroventricular administration of DBI or derived peptides induces proconflict and anxiety-like behaviors, and reduces food intake. Reciprocally, the expression of DBI/ACBP mRNA is regulated by stress and metabolic signals. In vitro, endozepines stimulate astrocyte proliferation and protect neurons and astrocytes from apoptotic cell death. Endozepines also regulate neurosteroid biosynthesis and neuropeptide expression, and promote neurogenesis. In peripheral organs, endozepines activate steroid hormone production, stimulate acyl chain ceramide synthesis and trigger pro-inflammatory cytokine secretion. The expression of the DBI/ACBP gene is enhanced in addiction/withdrawal animal models, in patients with neurodegenerative disorders and in various types of tumors. We review herein the current knowledge concerning the various actions of endozepines and discuss the physiopathological implications of these regulatory gliopeptides.

Endogenous Expression of ODN-Related Peptides in Astrocytes Contributes to Cell Protection Against Oxidative Stress: Astrocyte-Neuron Crosstalk Relevance for Neuronal Survival.

Astroglial cells are important actors in the defense of brain against oxidative stress injuries. Glial cells synthesize and release the octadecaneuropeptide ODN, a diazepam-binding inhibitor (DBI)-related peptide, which acts through its metabotropic receptor to protect neurons and astrocytes from oxidative stress-induced apoptosis. The purpose of the present study is to examine the contribution of the endogenous ODN in the protection of astrocytes and neurons from moderate oxidative stress. The administration of H2O2 (50 µM, 6 h) induced a moderate oxidative stress in cultured astrocytes, i.e., an increase in reactive oxygen species, malondialdehyde, and carbonyl group levels, but it had no effect on astrocyte death. Mass spectrometry and QPCR analysis revealed that 50 µM H2O2 increased ODN release and DBI mRNA levels. The inhibition of ODN release or pharmacological blockage of the effects of ODN revealed that in these conditions, 50 µM H2O2 induced the death of astrocytes. The transfection of astrocytes with DBI siRNA increased the vulnerability of cells to moderate stress. Finally, the addition of 1 nM ODN to culture media reversed cell death observed in DBI-deficient astrocytes. The treatment of neurons with media from 50 µM H2O2-stressed astrocytes significantly reduced the neuronal death induced by H2O2; this effect is greatly attenuated by the administration of an ODN metabotropic receptor antagonist. Overall, these results indicate that astrocytes produce authentic ODN, notably in a moderate oxidative stress situation, and this glio- and neuro-protective agent may form part of the brain defense mechanisms against oxidative stress injury.

Ketamine and Etomidate Down-regulate the Hypothalamic-Pituitary-Adrenal Axis in an Endotoxemic Mouse Model.

BACKGROUND: We compared the effects of etomidate and ketamine on the hypothalamic-pituitary-adrenal axis during sepsis. METHODS: Mice (n = 5/group) were injected intraperitoneally with lipopolysaccharide (10 mg/kg) and 6 h later randomized to receive ketamine (100 mg/kg), etomidate (30 mg/kg), or saline. At two time points (12 and 48 h), messenger RNA levels of hypothalamic corticotropin-releasing hormone, pituitary proopiomelanocortin, and four adrenal enzymes (P450 side-chain cleavage, 3ß-hydroxysteroid deshydrogenase, 21-hydroxylase, and 11ß-hydroxylase) were measured by in situ hybridization (results are presented as optical density), and plasma levels of corticosterone and adrenocorticotropin hormones were measured by enzyme-linked immunosorbent assay (mean ± SD). RESULTS: At 12 h, lipopolysaccharide induced an overexpression of corticotropin-releasing hormone (32 ± 5 vs. 18 ± 6, P < 0.01), proopiomelanocortin (21 ± 3 vs. 8 ± 0.9, P < 0.0001), P450 side-chain cleavage (32 ± 4 vs. 23 ± 10, P < 0.05), 21-hydroxylase (17 ± 5 vs. 12 ± 2, P < 0.05), and 11ß-hydroxylase (11 ± 4 vs. 6 ± 0.5, P = 0.001), and an elevation of corticosterone (642 ± 165 vs. 98.3 ± 63 ng/ml, P < 0.0001). Etomidate and ketamine reduced P450 side-chain cleavage (19 ± 7 and 19 ± 3 vs. 32 ± 4, P < 0.01), 21-hydroxylase (8 ± 0.8 and 8 ± 1 vs. 17 ± 5, P < 0.001), 11ß-hydroxylase (4 ± 0.5 and 7 ± 1 vs. 11 ± 4, P < 0.001 and P < 0.05), and corticosterone (413 ± 189 and 260 ± 161 vs. 642 ± 165 ng/ml, P < 0.05 and P < 0.01). Ketamine also inhibited adrenocorticotropin hormone production (2.5 ± 3.6 vs. 36 ± 15 pg/ml, P < 0.05). At 48 h, all four adrenal enzymes were down-regulated by lipopolysaccharide administration with corticosterone levels similar to the control group. Ketamine and etomidate did not modify corticosterone plasma levels. CONCLUSIONS: Our endotoxemic model induces an initial activation of the hypothalamic-pituitary-adrenal axis, followed by a secondary inhibition of adrenal steroidogenesis processes. Ketamine and etomidate inhibit the enzyme expression and activity of the adrenal gland at the early stage.

The G Protein-Coupled Receptor UT of the Neuropeptide Urotensin II Displays Structural and Functional Chemokine Features.

The urotensinergic system was previously considered as being linked to numerous physiopathological states, including atherosclerosis, heart failure, hypertension, pre-eclampsia, diabetes, renal disease, as well as brain vascular lesions. Thus, it turns out that the actions of the urotensin II (UII)/G protein-coupled receptor UT system in animal models are currently not predictive enough in regard to their effects in human clinical trials and that UII analogs, established to target UT, were not as beneficial as expected in pathological situations. Thus, many questions remain regarding the overall signaling profiles of UT leading to complex involvement in cardiovascular and inflammatory responses as well as cancer. We address the potential UT chemotactic structural and functional definition under an evolutionary angle, by the existence of a common conserved structural feature among chemokine receptorsopioïdergic receptors and UT, i.e., a specific proline position in the transmembrane domain-2 TM2 (P2.58) likely responsible for a kink helical structure that would play a key role in chemokine functions. Even if the last decade was devoted to the elucidation of the cardiovascular control by the urotensinergic system, we also attempt here to discuss the role of UII on inflammation and migration, likely providing a peptide chemokine status for UII. Indeed, our recent work established that activation of UT by a gradient concentration of UII recruits Gαi/o and Gα13 couplings in a spatiotemporal way, controlling key signaling events leading to chemotaxis. We think that this new vision of the urotensinergic system should help considering UT as a chemotactic therapeutic target in pathological situations involving cell chemoattraction.