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Opioid receptors are G protein-coupled receptors (GPCRs) that modulate brain function at all levels of neural integration, including autonomic, sensory, emotional and cognitive processing. Mu (MOR) and delta (DOR) opioid receptors functionally interact in vivo, but whether interactions occur at circuitry, cellular or molecular levels remains unsolved. To challenge the hypothesis of MOR/DOR heteromerization in the brain, we generated redMOR/greenDOR double knock-in mice and report dual receptor mapping throughout the nervous system. Data are organized as an interactive database offering an opioid receptor atlas with concomitant MOR/DOR visualization at subcellular resolution, accessible online. We also provide co-immunoprecipitation-based evidence for receptor heteromerization in these mice. In the forebrain, MOR and DOR are mainly detected in separate neurons, suggesting system-level interactions in high-order processing. In contrast, neuronal co-localization is detected in subcortical networks essential for survival involved in eating and sexual behaviors or perception and response to aversive stimuli. In addition, potential MOR/DOR intracellular interactions within the nociceptive pathway offer novel therapeutic perspectives.

Over-the-air (OTA) testing is crucial for optimizing wireless performance of 5G smart watches and improving their user experience. However, the current required test time is so long that it is almost impossible to complete the entire OTA testing without recharging and repositioning, which is unacceptable for the industry. Therefore, test-time reduction is significant. The objective of this work is to optimize measurement grids for OTA testing of 5G smart watches, which balance accuracy with efficiency. In this research, passive patterns from a typical 5G commercial smart watch are measured at different bands as reference patterns, which represent general radiation properties of 5G commercial smart watches. The effect of various coarse grids on OTA testing precision is characterized quantitatively by analyzing their accuracy in reconstructing reference patterns. The related measurement uncertainty (MU) terms are then evaluated and determined quantitatively based on statistical analysis. According to the derived MU limits for grid configurations, reducing grid points from currently required 62 (30/30) to 26 (45/45), and from 266 (15/15) to 62 (30/30) could save roughly 60% and 75% of the test time, respectively, with an uncertainty increase of 0.1 dB for both Total Isotropic Sensitivity (TIS) and Total Radiated Power (TRP) testing, which is considered acceptable. Furthermore, the feasibility of the proposed MU analysis and recommended grids have been experimentally verified.

In this paper we present the theoretical and experimental comparison of two digital controllers intended for stabilization of a two-wheeled robot. The properties of an LQG controller and an LQR controller with H ∞ filter are evaluated. Using the μ -analysis, we show that both controllers ensure robust stability of the closed-loop system in the presence of unstructured uncertainty. The results from the closed-loop system experimental evaluation confirm the precise work of both controllers.

μ-opioid receptor (MOR) is a class of opioid receptors that is critical for analgesia, reward, and euphoria. MOR is distributed in various brain regions, including the hippocampus, where traditionally, it is believed to be localized mainly at the presynaptic terminals of the GABAergic inhibitory interneurons to exert a strong disinhibitory effect on excitatory pyramidal neurons. However, recent intensive research has uncovered the existence of MOR in hippocampal astrocytes, shedding light on how astrocytic MOR participates in opioid signaling via glia-neuron interaction in the hippocampus. Activation of astrocytic MOR has shown to cause glutamate release from hippocampal astrocytes and increase the excitability of presynaptic axon fibers to enhance the release of glutamate at the Schaffer Collateral-CA1 synapses, thereby, intensifying the synaptic strength and plasticity. This novel mechanism involving astrocytic MOR has been shown to participate in hippocampus-dependent conditioned place preference. Furthermore, the signaling of hippocampal MOR, whose action is sexually dimorphic, is engaged in adult neurogenesis, seizure, and stress-induced memory impairment. In this review, we focus on the two profoundly different hippocampal opioid signaling pathways through either GABAergic interneuronal or astrocytic MOR. We further compare and contrast their molecular and cellular mechanisms and their possible roles in opioid-associated conditioned place preference and other hippocampus-dependent behaviors.

Monte-Carlo simulations play a key role in the current Attitude and Orbit Control Systems (AOCS) Verification and Validation (V&V) process, but it is generally time-consuming and it may fail in detecting worst-case configurations, especially in the presence of rare events. In such a case, μ-analysis offers a nice alternative, although it cannot measure the probability of occurrence of the identified worst-cases, which can invalidate a control system on the basis of unlikely events. Probabilistic μ-analysis was introduced in this context 20 years ago to bridge the gap between the two techniques, but until recently no practical tools were available. This paper summarizes recent advances on this topic with a particular emphasis on practical applications to space systems. More precisely, the proposed technique is applied to evaluate AOCS controllers in the context of a challenging high accuracy satellite pointing control problem. The way the proposed tools can be integrated into the traditional AOCS V&V process and used to tighten the V&V analysis gap is also highlighted.

Because of their great energy density and efficiency, lithium-ion batteries (LIBs) are essential to renewable energy systems and electric vehicles. Effective battery management requires precise estimation of the state of health (SoH) and state of charge (SoC). In order to overcome the difficulties caused by parameter fluctuations and real-world disturbances, this work presents a novel μ-analysis-based methodology designed to improve the resilience and accuracy of online SoC and SoH estimations in LIBs. In contrast to conventional techniques, the suggested strategy successfully manages both structured and unstructured uncertainties in battery systems by combining μ-analysis with model-based estimation. The framework creates an estimator that is resistant to parameter drift and outside perturbations by combining model-based estimation approaches with μ-analysis tools. Simulations using UDDS, US06, and HWFET driving cycles are used to verify its performance. When evaluating battery health and condition in dynamic and uncertain operating scenarios, the μ-analysis-based estimator demonstrates superior accuracy compared to conventional H∞-pole placement filter methods. The proposed approach enhances system robustness, achieving an 8 dB improvement in disturbance attenuation, as verified through MATLAB/Simulink. Stability analysis reveals the μ-analysis controller maintains robust performance up to ‖∆‖∞ = 3.5 at 10 Hz, compared to only ‖∆‖∞ = 1.5 for the H∞-pole placement controller—demonstrating significantly greater tolerance to parameter variations and unmodeled dynamics. These capabilities make the μ-analysis approach particularly suitable for electric vehicle applications requiring next-generation battery management systems.

The intrinsic efficacy of orthosteric ligands acting at G-protein-coupled receptors (GPCRs) reflects their ability to stabilize active receptor states (R*) and is a major determinant of their physiological effects. Here, we present a direct way to quantify the efficacy of ligands by measuring the binding of a R*-specific biosensor to purified receptor employing interferometry. As an example, we use the mu-opioid receptor (µ-OR), a prototypic class A GPCR, and its active state sensor, nanobody-39 (Nb39). We demonstrate that ligands vary in their ability to recruit Nb39 to µ-OR and describe methadone, loperamide, and PZM21 as ligands that support unique R* conformation(s) of µ-OR. We further show that positive allosteric modulators of µ-OR promote formation of R* in addition to enhancing promotion by orthosteric agonists. Finally, we demonstrate that the technique can be utilized with heterotrimeric G protein. The method is cell-free, signal transduction-independent and is generally applicable to GPCRs.

In this study, we created an accurate model for a homogenous smart structure. After modeling multiplicative uncertainty, an ideal robust controller was designed using μ-synthesis and a reduced-order H-infinity Feedback Optimal Output (Hifoo) controller, leading to the creation of an improved uncertain plant. A powerful controller was built using a larger plant that included the nominal model and corresponding uncertainty. The designed controllers demonstrated robust and nominal performance when handling agitated plants. A comparison of the results was conducted. As an example of a general smart structure, the vibration of a collocated piezoelectric actuator and sensor was controlled using two different approaches with strong controller designs. This study presents a comprehensive simulation of the oscillation suppression problem for smart beams. They provide an analytical demonstration of how uncertainty is introduced into the model. The desired outcomes were achieved by utilizing Simulink and MATLAB (v. 8.0) programming tools.

The main contribution of this paper is to present a new approach to the analysis of the absolute stability of multiple-input–multiple-output (MIMO) Lurie-type systems using μ-analysis and linear fractional transformations from the robust control theory. As a consequence, and also as an important contribution, the technique proposed enables the design of controllers via DK-Iteration for Lurie-type systems. For these, one extends the results obtained for Lurie-type systems to a closed-loop version of it. In addition, it is also conjectured that it is possible to make use of this new approach in time-delay MIMO Lurie-type systems. The obtained results allow a generalization of the theory for the analysis and design of controllers that can be useful in complex networks. Examples and comparisons with other results are given to illustrate the effectiveness of the methods of this paper.

The presence of endogenous opioid peptides in different testicular cell types has been extensively characterized and provides evidence for the participation of the opioid system in the regulation of testicular function. However, the exact role of the opioid system during the spermatogenesis has remained controversial since the presence of the mu-, delta- and kappa-opioid receptors in spermatogenic cells was yet to be demonstrated. Through a combination of quantitative real-time PCR, immunofluorescence, immunohistochemistry and flow cytometry approaches, we report for the first time the presence of active mu-, delta- and kappa-opioid receptors in mouse male germ cells. They show an exposition time-dependent response to opioid agonist, hence suggesting their active involvement in spermatogenesis. Our results contribute to understanding the role of the opioid receptors in the spermatogenesis and could help to develop new strategies to employ the opioid system as a biochemical tool for the diagnosis and treatment of male infertility.