Search Results (433)

This survey provides a comprehensive review of the integration of large language models (LLMs) into autonomous robotic systems, organized around four key pillars: locomotion, navigation, manipulation, and voice-based interaction. We examine how LLMs enhance robotic autonomy by translating high-level natural language commands into low-level control signals, supporting semantic planning and enabling adaptive execution. Systems like SayTap improve gait stability through LLM-generated contact patterns, while TrustNavGPT achieves a 5.7% word error rate (WER) under noisy voice-guided conditions by modeling user uncertainty. Frameworks such as MapGPT, LLM-Planner, and 3D-LOTUS++ integrate multi-modal data—including vision, speech, and proprioception—for robust planning and real-time recovery. We also highlight the use of physics-informed neural networks (PINNs) to model object deformation and support precision in contact-rich manipulation tasks. To bridge the gap between simulation and real-world deployment, we synthesize best practices from benchmark datasets (e.g., RH20T, Open X-Embodiment) and training pipelines designed for one-shot imitation learning and cross-embodiment generalization. Additionally, we analyze deployment trade-offs across cloud, edge, and hybrid architectures, emphasizing latency, scalability, and privacy. The survey concludes with a multi-dimensional taxonomy and cross-domain synthesis, offering design insights and future directions for building intelligent, human-aligned robotic systems powered by LLMs. Full article

Patients with ulcerative colitis exhibit an increased risk for supraventricular arrhythmia during the active disease phase of the disease and show signs of atrial electrophysiological remodeling in remission. The goal of this study was to determine the basis for colitis-induced changes in atrial excitability. In a mouse model (C57BL/6; 3 months) of dextran sulfate sodium (DSS)-induced active colitis (3.5% weight/volume, 7 days), electrocardiograms (ECG) revealed altered atrial electrophysiological properties with a prolonged P-wave duration and PR interval. ECG changes coincided with a decreased atrial conduction velocity in Langendorff perfused hearts. Action potentials (AP) recorded from isolated atrial myocytes displayed an attenuated maximal upstroke velocity and amplitude during active colitis, as well as a prolonged AP duration (APD). Voltage clamp analysis revealed a colitis-induced shift in the voltage-dependent activation of the Na-current (I_Na) to more depolarizing voltages. In addition, protein levels of Na_v1.5 protein and connexin isoform Cx43 were reduced. APD prolongation depended on a reduction in the transient outward K-current (I_to) mostly generated by K_v4.2 channels. The changes in ECG, atrial conductance, and APD were reversible upon remission. The change in conduction velocity predominantly depended on the reversibility of the reduced Cx43 and Na_v1.5 expression. Treatment of mice with inhibitors of Angiotensin-converting enzyme (ACE) or Angiotensin II (AngII) receptor type 1 (AT1R) prevented the colitis-induced atrial electrophysiological remodeling. Our data support a colitis-induced increase in AngII signaling that promotes atrial electrophysiological remodeling and puts colitis patients at an increased risk for atrial arrhythmia. Full article

European integration aims to achieve spatially sustainable development across the member states. However, the success of socio-economic integration is conditioned by structural features of the economies, which, hitherto, appear highly diversified across the EU countries. The paper focuses on the structural conditions of the process of income inequality convergence. It aims to identify differences in the convergence regarding the structural conditions of the economies. To fulfil the research tasks the paper classifies the 27 European member states according to their sectional employment structures using the Ward method. It then tests the appearance of beta convergence using FE panel models for the specified clusters of economies. It also considers structural change, measured by the NAV (norm of absolute value), as a determinant of income inequality convergence. The main research period covers 2009–2021. The findings of the paper confirm that income inequality convergence occurs within the groups of economies specified by different structural conditions. Importantly, the clustering according to the similarity of the employment structure overlaps with the division along the lines of the ‘new’ and ‘old’ member states, which proves the importance of historically shaped institutions for development. However, the observed convergence does not lead to improved social cohesion. Social policy, especially in the ‘new’ member states, is not able to offset the growth in market income inequality additionally stimulated by the structural changes. It can be concluded that an urgent need to design new solutions for social policy concerning structural transformation in employment in the EU emerges. Full article

Off-road path planning involves navigating vehicles through areas lacking established road networks, which is critical for emergency response in disaster events, but is limited by the complex geographical environments in natural conditions. How to model the vehicle’s off-road mobility effectively and represent environments is critical for efficient path planning in off-road environments. This paper proposed an improved A* path planning algorithm based on a Delaunay triangular NavMesh model with off-road environment representation. Firstly, a land cover off-road mobility model is constructed to determine the navigable regions by quantifying the mobility of different geographical factors. This model maps passable areas by considering factors such as slope, elevation, and vegetation density and utilizes morphological operations to minimize mapping noise. Secondly, a Delaunay triangular NavMesh model is established to represent off-road environments. This mesh leverages Delaunay triangulation’s empty circle and maximum-minimum angle properties, which accurately represent irregular obstacles without compromising computational efficiency. Finally, an improved A* path planning algorithm is developed to find the optimal off-road mobility path from a start point to an end point, and identify a path triangle chain with which to calculate the shortest path. The improved road-off path planning A* algorithm proposed in this paper, based on the Delaunay triangulation navigation mesh, uses the Euclidean distance between the midpoint of the input edge and the midpoint of the output edge as the cost function $g\left(n\right)$, and the Euclidean distance between the centroids of the current triangle and the goal as the heuristic function $h\left(n\right)$. Considering that the improved road-off path planning A* algorithm could identify a chain of path triangles for calculating the shortest path, the funnel algorithm was then introduced to transform the path planning problem into a dynamic geometric problem, iteratively approximating the optimal path by maintaining an evolving funnel region, obtaining a shortest path closer to the Euclidean shortest path. Research results indicate that the proposed algorithms yield optimal path-planning results in terms of both time and distance. The navigation mesh-based path planning algorithm saves 5~20% of path length than hexagonal and 8-directional grid algorithms used widely in previous research by using only 1~60% of the original data loading. In general, the path planning algorithm is based on a national-level navigation mesh model, validated at the national scale through four cases representing typical natural and social landscapes in China. Although the algorithms are currently constrained by the limited data accessibility reflecting real-time transportation status, these findings highlight the generalizability and efficiency of the proposed off-road path-planning algorithm, which is useful for path-planning solutions for emergency operations, wilderness adventures, and mineral exploration. Full article

Suzetrigine represents a groundbreaking advancement in acute pain management as the first FDA-approved selective Na_v1.8 inhibitor. This comprehensive review synthesizes data from clinical trials, pharmacological studies, and prescribing information to evaluate its mechanism, efficacy, safety, and clinical implications. With demonstrated superiority over placebo in pivotal trials (SPID48: 29.3–48.4; p < 0.0001) and a favorable safety profile devoid of opioid-like addiction risks, suzetrigine offers a much-needed alternative in the opioid crisis era. However, its modest effect size compared to full-dose opioids, CYP3A-mediated drug interactions, and limited long-term data warrant judicious use. This article provides a balanced perspective on suzetrigine’s role in modern pain management protocols. Full article

Saxitoxin (STX) is a potent toxin produced by marine dinoflagellates and freshwater or brackish water cyanobacteria, and is a member of the paralytic shellfish toxins (PSTs). As a highly specific blocker of voltage-gated sodium channels (NaVs), STX blocks sodium ion influx, thereby inhibiting nerve impulse transmission and leading to systemic physiological dysfunctions in the nervous, respiratory, cardiovascular, and digestive systems. Severe exposure can lead to paralysis, respiratory failure, and mortality. STX primarily enters the human body through the consumption of contaminated shellfish, posing a significant public health risk as the causative agent of paralytic shellfish poisoning (PSP). Beyond its acute toxicity, STX exerts cascading impacts on food safety, marine ecosystem integrity, and economic stability, particularly in regions affected by harmful algal blooms (HABs). Moreover, the complex molecular structure of STX—tricyclic skeleton and biguanide group—and its diverse analogs (more than 50 derivatives) have made it the focus of research on natural toxins. In this review, we traced the discovery history, chemical structure, molecular biosynthesis, biological enrichment mechanisms, and toxicological actions of STX. Moreover, we highlighted recent advancements in the potential for detection and treatment strategies of STX. By integrating multidisciplinary insights, this review aims to provide a holistic understanding of STX and to guide future research directions for its prevention, management, and potential applications. Full article

Autonomous Vehicles (AV) have been extensively studied in both scientific and social contexts. Over the past two decades, there has been a significant rise in their real-world applications, including neural networks, Blockchain, Internet of Things, autonomous navigation, computer vision, automation processes, and various other areas. Hence, it is imperative to investigate the interplay between software, hardware, and individuals. To guarantee secure and unaffected interactions within autonomous vehicle devices and networks, decentralized Blockchain technology is proposed. This study presents the introduction of a framework we named “DEMU-NAV” for an ecosystem that includes Artificial Intelligence (AI), humans, and robots. The framework makes use of a decentralized Blockchain, Smart-Contract (SC), and Internet of things (IoT) network. Our framework was implemented using Ethereum and Python, enabling us to oversee Blockchain, Smart-Contracts, and the IoT for the facilitation of autonomous vehicle navigation. Full article

The objective of the present study was to evaluate and compare the accuracy of the computer-aided static navigation technique (NAV), augmented reality (AR) and freehand placement technique (FHT) for the bicortical orthodontic self-drilling mini-implants for maxillary skeletal expansion (MSE) appliances placed in palate. Material and Methods: A total of 120 bicortical orthodontic self-drilling mini-implants were placed in the palate of ten 3D printed anatomically based polyurethane models of a completely edentulous upper maxilla. The orthodontic mini-implants were randomly assigned to the following placement techniques: (A) computer-aided static navigation technique (n = 40) (NAV), (B) augmented reality device (n = 40) (AR) and (C) conventional freehand technique (n = 40) (FHT). Moreover, two implants were placed in each side of the midpalatal suture in every model according to the digital planification of the expander device. Subsequently, the orthodontic mini-implants were placed and postoperative CBCT scans were performed. Finally, coronal entry-point (mm), apical end-point (mm) and angular deviations (°) were calculated using a t-test. Results: Statistically significant differences were shown at coronal entry-point (p < 0.001), apical end-point (p < 0.001) and angular deviations (p < 0.001) between the three placement techniques of bicortical orthodontic mini-implants. Additionally, statistically significant differences were also shown between the orthodontic mini-implant positions concerning the entry point (p = 0.004) and angular deviation (p = 0.004). Conclusions: The augmented reality placement technique results are more accurate, followed by the computer-aided static navigation technique and the freehand technique for MSE appliances placed in palate. Full article

Accelerating the recovery of compacted soils caused by logging machinery using bioengineering techniques is a key goal of Sustainable Forest Management. This research was conducted on an abandoned skid trail with a uniform 15% slope and a history of heavy traffic, located in the Nav forest compartment of northern Iran. The main objectives were to assess (a) soil physical properties 35 years after skidding by a tracked bulldozer, (b) the impact of natural alder regeneration on soil recovery, and (c) the contribution of alder fine-root development to the restoration of compacted soils in beech stands. Soil physical properties and fine root biomass were analyzed across three depth classes (0–10 cm, 10–20 cm, 20–30 cm) and five locations (left wheel track (LT), between wheel tracks (BT), right wheel track (RT)) all with alder trees, and additionally control points inside the trail without alder trees (CPWA), as well as outside control points with alder trees (CPA). Sampling points near alder trees (RT, LT, BT) were compared to CPWA and CPA. CPA had the lowest soil bulk density, followed by LT, BT, RT, and CPWA. Bulk density was highest (1.35 ± 0.07 g cm⁻³) at the 0–10 cm depth and lowest (1.08 ± 0.4 g cm⁻³) at 20–30 cm. The fine root biomass at 0–10 cm depth (0.23 ± 0.21 g dm⁻³) was significantly higher than at deeper levels. Skid trail sampling points showed higher fine root biomass than CPWA but lower than CPA, by several orders of magnitude. Alder tree growth significantly reduced soil bulk density, aiding soil recovery in the study area. However, achieving optimal conditions will require additional time. Full article

Anesthesia is a cornerstone of modern medicine, enabling surgery, pain management, and critical care. Despite its widespread use, the precise molecular mechanisms of anesthetic action remain incompletely understood. Recent advancements in structural biology, including cryo-electron microscopy (Cryo-EM), X-ray crystallography, and computational modeling, have provided high-resolution insights into anesthetic–target interactions. This review examines key molecular targets, including GABA_A receptors, NMDA receptors, two-pore-domain potassium (K2P) channels (e.g., TREK-1), and voltage-gated sodium (Nav) channels. General anesthetics modulate GABA_A and NMDA receptors, affecting inhibitory and excitatory neurotransmission, while local anesthetics primarily block Nav channels, preventing action potential propagation. Structural studies have elucidated anesthetic binding sites and gating mechanisms, providing a foundation for drug optimization. Advances in computational drug design and AI-assisted modeling have accelerated the development of safer, more selective anesthetics, paving the way for precision anesthesia. Future research aims to develop receptor-subtype-specific anesthetics, Nav1.7-selective local anesthetics, and investigate the neural mechanisms of anesthesia-induced unconsciousness and postoperative cognitive dysfunction (POCD). By integrating structural biology, AI-driven drug discovery, and neuroscience, anesthesia research is evolving toward safer, more effective, and personalized strategies, enhancing clinical outcomes and patient safety. Full article

Indoor navigation remains a challenge due to the limitations of GPS-based systems in enclosed environments. Current approaches, such as marker-based ones, have been developed for indoor navigation. However, it requires extensive manual mapping and makes indoor navigation time-consuming and difficult to scale. To enhance current approaches to indoor navigation, this study proposes a node-based mapping for indoor navigation, allowing users to dynamically construct navigation paths using a mobile device. The system leverages NavMesh, the A* algorithm for pathfinding, and is integrated into the ARCore for real-time AR guidance. Nodes are placed within the environment to define walkable paths, which can be stored and reused without requiring a full system to rebuild. Once the prototype has been developed, usability testing is conducted using the Handheld Augmented Reality Usability Scale (HARUS) to evaluate manipulability, comprehensibility, and overall usability. This study finds that using node-based mapping for indoor navigation can help enhance flexibility in mapping new indoor spaces and offers an effective AR-guided navigation experience. However, there are some areas of improvement, including interface clarity and system scalability, that can be considered for future research. This study contributes practically to improving current practices in adaptive indoor navigation systems using AR-based dynamic mapping techniques. Full article

Neuropathic pain is a chronic and debilitating disorder of the somatosensory system that affects a significant proportion of the population and is characterized by abnormal responses such as hyperalgesia and allodynia. Voltage-gated ion channels, including sodium (Na_V), calcium (Ca_V), and potassium (K_V) channels, play a pivotal role in modulating neuronal excitability and pain signal transmission following nerve injury. This review intends to provide a comprehensive analysis of the molecular and cellular mechanisms by which dysregulation in the expression, localization, and function of specific Na_V channel subtypes (mainly Na_V1.7 and Na_V1.8) and their auxiliary subunits contributes to aberrant neuronal activation, the generation of ectopic discharges, and sensitization in neuropathic pain. Likewise, special emphasis is placed on the crucial role of Ca_V channels, particularly Ca_V2.2 and the auxiliary subunit Ca_Vα₂δ, whose overexpression increases calcium influx, neurotransmitter release, and neuronal hyperexcitability, thus maintaining persistent pain states. Furthermore, K_V channels (particularly K_V7 channels) function as brakes on neuronal excitability, and their dysregulation facilitates the development and maintenance of neuropathic pain. Therefore, targeting specific K_V channel subtypes to restore their function is also a promising therapeutic strategy for alleviating neuropathic pain symptoms. On the other hand, recent advances in the development of small molecules as selective modulators or inhibitors targeting voltage-gated ion channels are also discussed. These agents have improved efficacy and safety profiles in preclinical and clinical studies by attenuating pathophysiological channel activity and restoring neuronal function. This review seeks to contribute to guiding future research and drug development toward more effective mechanism-based treatments by discussing the molecular mechanisms underlying neuropathic pain and highlighting translational therapeutic opportunities. Full article

Background: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with a rising prevalence, driven by multifactorial genetic and environmental factors. Among the genetic contributors identified, SCN2A, a critical gene encoding the Nav1.2 sodium channel, has been implicated in ASD and other related neurological conditions. This systematic review aims to explore the relationship between SCN2A mutations and ASD phenotypes. Methods: This review systematically analyzed data from studies reporting SCN2A mutations in individuals diagnosed with ASD. The primary focus was on the characterization of mutation types, associated clinical features, and phenotypic variability. Results: The mutations identified were predominantly de novo missense mutations and were associated with a spectrum of neurological and developmental challenges, including seizures, intellectual disability, movement disorders, and repetitive behaviors. A notable finding was the significant phenotypic variability observed across individuals. Gender differences emerged, suggesting a potentially greater impact on females compared to trends typically seen in ASD genetic studies. Specific mutations, such as c.2919+4delT, and mosaicism were identified as novel contributors to the observed heterogeneity. Conclusions: The review highlights the clinical significance of SCN2A mutations in ASD and highlights their relevance in genetic counseling and the development of targeted therapies. Understanding the diverse genotype–phenotype correlations associated with SCN2A can drive progress in personalized medicine, paving the way for precision therapies tailored to individuals with SCN2A-related ASD. Full article

The voltage-gated sodium channel Na_v1.7 is essential for pain perception and is an interesting target for the development of pain-relieving substances. Here, we investigated whether the Na_v1.7 channel is sensitive to harmaline, an alkaloid produced by the North African plant Peganum harmala. To this end, we used Chinese hamster ovary (CHO) cells expressing the human Na_v1.7 channel and studied Na⁺ channel pharmacology with an automated patch-clamp technique. Cells stimulated with depolarizing voltage pulses responded with typical transient inward currents. The Na⁺ channel blocker ranolazine inhibited whole-cell currents in a concentration-dependent manner (IC₅₀: 12.1 µM). Harmaline inhibited both peak and late Na⁺ currents. A complete block was achieved at 300 µM of harmaline, with half maximum inhibition occurring at 35.5 µM. In contrast to ranolazine, the effect of harmaline was voltage independent. Neither the current/voltage curves nor the steady-state inactivation curves were shifted in response to drug application (30 µM). We conclude that the plant alkaloid harmaline, which is used in traditional medicine in North Africa, is an effective blocker of the voltage-gated Na⁺ channel Na_v1.7. Our results offer a rationale for the use of harmaline against certain pain syndromes and rise hopes for the development of a new class of anti-nociceptive drugs targeting Na_v1.7. Full article

The presence and function of the opioidergic system in sensory dorsal root ganglia (DRG) was demonstrated in various animal models of pain. To endorse recent functional and transcriptional evidence of opioid receptors in human DRG, this study compared morphological and transcriptional evidence in human and rat DRG using immunofluorescence confocal microscopy and mRNA transcript analysis. Specifically, it examined the neuronal expression of mu (MOR), delta (DOR), and kappa (KOR) opioid receptors, opioid peptide precursors (POMC, PENK, and PDYN), and key pain-signaling molecules. The results demonstrate abundant immunoreactivity in human DRG for key pain transduction receptors, including the thermosensitive ion channels TRPV1, TRPV4 and TRPA1, mechanosensitive PIEZO1 and PIEZO2, and the nociceptive-specific Nav1.8. They colocalized with calcitonin gene-related peptide (CGRP), a marker for peptidergic sensory neurons. Within this same subpopulation, we identified MOR, DOR, and KOR, while their ligand precursors were less abundant. Notably, the mRNA transcripts of MOR and PENK in human DRG were highest among the opioid-related genes; however, they were considerably lower than those of key pain-signaling molecules. These findings were corroborated by functional evidence in demonstrating the fentanyl-induced inhibition of voltage-gated calcium currents in rat DRG, which was antagonized by naloxone. The immunohistochemical and transcriptional demonstration of opioid receptors and their endogenous ligands in both human and rat DRG support recent electrophysiologic and in situ hybridization evidence in human DRG and confirms their potential as analgesic targets. This peripherally targeted approach has the advantage of mitigating central opioid-related side effects, endorsing the potential of future translational pain research from rodent models to humans. Full article