Locomotion Gaits Research Articles

Effect of patient specificity on predicting knee cartilage degeneration in obese adults: Musculoskeletal finite-element modeling of data from the CAROT trial.

Obesity is a known risk factor for development of osteoarthritis (OA). Numerical tools like finite-element (FE) models combined with degenerative algorithms have been developed to understand the interplay between OA and obesity. Inthisstudy,we aimed to predict knee cartilage degeneration in a cohort of obese adults to investigate the importance of patient-specific information on degeneration predictions. We used a validated FE modeling approach and three different age-dependent functions (step-wise, exponential, and linear) to simulate cartilage degradation under overloading in the knee joint. Gait motion analysis and magnetic resonance imaging data from 115 obese individuals with knee OA were used for musculoskeletal and FE modeling. Cartilage degeneration predictions were contrasted with Kellgren-Lawrence (KL)and Boston-Leeds Osteoarthritis Knee Score (BLOKS) grades. The findings show that overall, the similarities between numerical predictions and clinical measures were better for the medial (average area under the curve(AUC) = 0.62) compared to the lateral compartment (average AUC = 0.52) of the knee. Classification results for KL grades, full patient-specific models and patient-specific geometry with generic gait data showed higher AUC values (AUC = 0.71 and AUC = 0.68, respectively) compared to generic geometry and patient-specific gait (AUC = 0.48). For BLOKS grades, AUC values for both full patient-specific models and for patient-specific geometry with generic gait locomotion were higher (AUC = 0.66 and AUC = 0.64, respectively) compared to when the generic geometry and patient-specific gait were used (AUC = 0.53). In summary, our study highlights the importance of considering individual information in knee OA prediction. Nevertheless, our findings suggest that personalized gait play a smaller role in the OA prediction and classification capacity than personalized joint geometry.

A Novel Caterpillar-Inspired Vascular Interventional Robot Navigated by Magnetic Sinusoidal Mechanism

Magnetic soft continuum robots (MSCRs) hold significant potential in fulfilling the requirements of vascular interventional robots, enabling safe access to difficult-to-reach areas with enhanced active maneuverability, shape morphing capabilities, and stiffness variability. Their primary advantage lies in their tether-less actuation mechanism that can safely adapt to complex vessel structures. Existing commercial MSCRs primarily employ a magnetic-pull strategy, which suffers from insufficient driving force and a single actuation strategy, limiting their clinical applicability. Inspired by the inchworm crawling locomotion gait, we herein present a novel MSCR that integrates a magnetic sinusoidal actuation mechanism with adjustable frequency and kirigami structures. The developed MSCRs consist of two permanent magnets connected by a micro-spring, which is coated with a silicone membrane featuring a specific notch array. This design enables bio-inspired crawling with controllable velocity and active maneuverability. An analytical model of the magnetic torque and finite element analysis (FEA) simulations of the MSCRs has been constructed. Additionally, the prototype has been validated through two-dimensional in-vitro tracking experiments with actuation frequencies ranging from 1 to 10 Hz. Its stride efficiency has also been verified in a three-dimensional (3D) coronary artery phantom. Diametrically magnetized spherical chain tip enhances active steerability. Kirigami skin is coated over the novel guidewire and catheter, not only providing proximal anchorage for improved stride efficiency but also serving similar function as a cutting balloon. Under the actuation of an external magnetic field, the proposed MSCRs demonstrate the ability to traverse bifurcations and tortuous paths, indicating their potential for dexterous flexibility in pathological vessels.

Reconfigurable origami with variable stiffness joints for adaptive robotic locomotion and grasping.

With its compactness and foldability, origami has recently been applied to robotic systems to enable versatile robots and mechanisms while maintaining a low weight and compact form. This work investigates how to generate different motions and shapes for origami by tuning its creases' stiffness on the fly. The stiffness tuning is realized by a composite material made by sandwiching a thermoplastic layer between two shape memory polymer layers. This enables the composite to act as a living hinge, whose stiffness can be actively controlled through Joule heating. To demonstrate our concept, we fabricate an origami module with four variable stiffness joints (VSJs), allowing it to have freely controlled crease stiffnesses across its surface. We characterize the origami module's versatile motion when heating different VSJs with different temperatures. We further use two origami modules to build a two-legged robot that can locomote on the ground with different locomotion gaits. The same robot is also used as an adaptive gripper for grasping tasks. Our work can potentially enable more versatile robotic systems made from origami as well as other mechanical systems with programmable properties (e.g. mechanical metamaterials).This article is part of the theme issue 'Origami/Kirigami-inspired structures: from fundamentals to applications'.

Applying 3D Models of Giant Salamanders to Explore Form-Function Relationships in Early Digit-Bearing Tetrapods.

Extant salamanders are used as modern analogs of early digit-bearing tetrapods due to general similarities in morphology and ecology, but the study species have been primarily terrestrial and relatively smaller when the earliest digit-bearing tetrapods were aquatic and an order of magnitude larger. Thus, we created a 3D computational model of underwater walking in extant Japanese giant salamanders (Andrias japonicus) using 3D photogrammetry and open-access graphics software (Blender) to broaden the range of testable hypotheses about the incipient stages of terrestrial locomotion. Our 3D model and software protocol represent the initial stages of an open-access pipeline that could serve as a "one-stop-shop" for studying locomotor function, from creating 3D models to analyzing the mechanics of locomotor gaits. While other pipelines generally require multiple software programs to accomplish the different steps in creating and analyzing computational models of locomotion, our protocol is built entirely within Blender and fully customizable with its Python scripting so users can devote more time to creating and analyzing models instead of navigating the learning curves of several software programs. The main value of our approach is that key kinematic variables (e.g. speed, stride length, and elbow flexion) can be easily altered on the 3D model, allowing scientists to test hypotheses about locomotor function and conduct manipulative experiments (e.g. lengthening bones) that are difficult to perform in vivo. The accurate 3D meshes (and animations) generated through photogrammetry also provide exciting opportunities to expand the abundance and diversity of 3D digital animals available for researchers, educators, artists, conservation biologists, etc. to maximize societal impacts.

Electronically configurable microscopic metasheet robots.

Shape morphing is vital to locomotion in microscopic organisms but has been challenging to achieve in sub-millimetre robots. By overcoming obstacles associated with miniaturization, we demonstrate microscopic electronically configurable morphing metasheet robots. These metabots expand locally using a kirigami structure spanning five decades in length, from 10 nm electrochemically actuated hinges to 100 μm splaying panels making up the ~1 mm robot. The panels are organized into unit cells that can expand and contract by 40% within 100 ms. These units are tiled to create metasheets with over 200 hinges and independent electronically actuating regions that enable the robot to switch between multiple target geometries with distinct curvature distributions. By electronically actuating independent regions with prescribed phase delays, we generate locomotory gaits. These results advance a metamaterial paradigm for microscopic, continuum, compliant, programmable robots and pave the way to a broad spectrum of applications, including reconfigurable micromachines, tunable optical metasurfaces and miniaturized biomedical devices.

Postural control depends on early visual experience.

The present study investigated the role of early visual experience in the development of postural control (balance) and locomotion (gait). In a cross-sectional design, balance and gait were assessed in 59 participants (ages 7-43 years) with a history of (a) transient congenital blindness, (b) transient late-onset blindness, (c) permanent congenitally blindness, or (d) permanent late-onset blindness, as well as in normally sighted controls. Cataract-reversal participants who experienced a transient phase of blindness and gained sight through cataract removal surgery showed worse balance performance compared with sighted controls even when tested with eyes closed. Individuals with reversed congenital cataracts performed worse than individuals with reversed developmental (late emerging) cataracts. Balance performance in congenitally cataract-reversal participants when tested with eyes closed was not significantly different from that in permanently blind participants. In contrast, their gait parameters did not differ significantly from those of sighted controls. The present findings highlight both the need for visual calibration of proprioceptive and vestibular systems and the crossmodal adaptability of locomotor functions.

Sensory feedback and central neuronal interactions in mouse locomotion.

Locomotion is a complex process involving specific interactions between the central neural controller and the mechanical components of the system. The basic rhythmic activity generated by locomotor circuits in the spinal cord defines rhythmic limb movements and their central coordination. The operation of these circuits is modulated by sensory feedback from the limbs providing information about the state of the limbs and the body. However, the specific role and contribution of central interactions and sensory feedback in the control of locomotor gait and posture remain poorly understood. We use biomechanical data on quadrupedal locomotion in mice and recent findings on the organization of neural interactions within the spinal locomotor circuitry to create and analyse a tractable mathematical model of mouse locomotion. The model includes a simplified mechanical model of the mouse body with four limbs and a central controller composed of four rhythm generators, each operating as a state machine controlling the state of one limb. Feedback signals characterize the load and extension of each limb as well as postural stability (balance). We systematically investigate and compare several model versions and compare their behaviour to existing experimental data on mouse locomotion. Our results highlight the specific roles of sensory feedback and some central propriospinal interactions between circuits controlling fore and hind limbs for speed-dependent gait expression. Our models suggest that postural imbalance feedback may be critically involved in the control of swing-to-stance transitions in each limb and the stabilization of walking direction.

Locomotion gait control of snake robots based on a novel unified CPG network model composed of Hopf oscillators

Snake robots with limbless structure and rich locomotion gaits have been designed and built for wide application in various fields including military reconnaissance, pipeline operation, disaster search and rescue, etc. However, the problem how to flexibly and smoothly control switch and change of different locomotion gaits is still facing enormous challenges. A novel unified design rule of the CPG network model composed of improved Hopf oscillators is proposed, based on which a variety of different network structures can be created by designing connection distances and coupling weights among all oscillator units. Through the relationships between the control parameters of the Hopf oscillator, decoupling of the bifurcation parameters is achieved to solve inconsistent output waveform amplitude when the bifurcation parameters are not completely equal. Furthermore, five typical movement modes of biological snake are designed and smooth switch between different locomotion gaits is realized. A control system is constructed based on the Robot Operating System (ROS) and a prototype of snake robot is built, and the effectiveness of the proposed CPG model in controlling locomotion gaits was verified through simulations and experiments. The CPG modeling approach has important theoretical significance and practical instructive value for motion planning and gait control of snake robots in complex environments.

Curcumin analogue NL04 inhibits spinal cord central sensitization in rats with bone cancer pain by inhibiting NLRP3 inflammasome activation and reducing IL-1β production

The management and therapy of bone cancer pain (BCP) remain formidable clinical challenges. Curcumin and its analogues have been shown to have anti-inflammatory and analgesic properties. In the present study, we investigated the efficacy of curcumin analogue NL04 (NL04) in modulating inflammation in spinal dorsal horn (SDH), thereby exploring its potential to reduce central sensitization of BCP in a rat model. Differing doses of NL04 and curcumin were administered intrathecally either once (on day 12 of BCP) or over seven consecutive days (from day 6–12 of BCP). Results indicated that the ED50 for NL04 and curcumin ameliorating BCP-induced mechanical hyperalgesia is 49.08 μg/kg and 489.6 μg/kg, respectively. The analgesic effects at various doses of NL04 lasted between 4 and 8 h, with sustained administration over a week maintaining pain relief for 1–4 days, while also ameliorating locomotor gait via gait analysis and reducing depressive and anxiety-like behaviors via open-field and light–dark transition tests. The analgesic effects at various doses of curcumin lasted 4 h, with sustained administration over a week maintaining pain relief for 0–2 days. ELISA, Western blotting, qPCR, and immunofluorescence assays substantiated that intrathecal administration of NL04 on days 6–12 of BCP dose-dependently lowered spinal IL-1β and IL-18 levels and significantly reduced the expression of IKKβ genes and proteins, as well as the downstream cleavage of the trans-Golgi network (TGN). Whole-cell patch-clamp results demonstrated that NL04 inhibits potassium ion efflux in rat primary spinal neurons. Thus, NL04 exhibits significant analgesic effects in a BCP rat model by downregulating IKKβ expression and inhibiting neuronal potassium ion efflux, which, in turn, suppresses the activation of NLRP3 inflammasomes and reduces IL-1β production, potentially ameliorating pain management in BCP.

Automatic Holonomic Mobile Micromanipulator for Submillimeter Objects Inspired by the Rhinoceros Beetle

Holonomic mobile micromanipulators driven by piezoelectric actuators offer precision and compact design. However, attaining both high speed and positioning repeatability with sufficient load capacity poses challenges, given that lightweight robots are susceptible to nonuniform driving surfaces and external forces. A holonomic beetle (HB) is proposed to realize a wide range, compact size, precise holonomic motion, automatic micromanipulation, and high‐speed movement simultaneously. Inspired by the biological makeup of a Rhinoceros Beetle, a length, weight, and load capacity of 8 cm, 74 g, and of 2000 g, respectively, are used. The HB is a two‐legged robot with a pseudoalternating tripod gait locomotion principle, with five piezoelectric actuators for XYθ displacement and switching of the contact leg. It achieves maximum walking velocities of 11.6 mm s−1 for translational motion and 19.3 deg s−1 for rotation, with a displacement resolution of 12 nm. Notably, under open‐loop control, the HB demonstrates high repeatability with a coefficient of variation of 0.3%. It exhibits the capability to climb 30°‐inclined surfaces, traverse flat surfaces with 0.1 mm bumps, and navigate 30 mm pits. Furthermore, the HB showcases practical automatic micromanipulation through visual servo control and machine learning, presenting potential applications in biomedical and microassembly fields.

Design, Optimization, and Modeling of a Hydraulic Soft Robot for Chronic Total Occlusions.

Chronic total occlusion (CTO) is one of the most severe and sophisticated vascular stenosis because of complete blockage, greater operation difficulty, and lower procedural success rate. This study proposes a hydraulic-driven soft robot imitating the earthworm's locomotion to assist doctors or operators in actively opening thrombi in coronary or peripheral artery vessels. Firstly, a three-actuator bionic soft robot is developed based on earthworms' physiological structure. The soft robot's locomotion gait inspired by the earthworm's mechanism is designed. Secondly, the influence of structure parameters on actuator deformation, stress, and strain is explored, which can help us determine the soft actuators' optimal structure parameters. Thirdly, the relationship between hydraulic pressure and actuator deformation is investigated by performing finite element analysis using the bidirectional fluid-structure interaction (FSI) method. The kinematic models of the soft actuators are established to provide a valuable reference for the soft actuators' motion control.

Multimodal Soft Robotic Actuation and Locomotion.

Diverse and adaptable modes of complex motion observed at different scales in living creatures are challenging to reproduce in robotic systems. Achieving dexterous movement in conventional robots can be difficult due to the many limitations of applying rigid materials. Robots based on soft materials are inherently deformable, compliant, adaptable, and adjustable, making soft robotics conducive to creating machines with complicated actuation and motion gaits. This review examines the mechanisms and modalities of actuation deformation in materials that respond to various stimuli. Then, strategies based on composite materials are considered to build toward actuators that combine multiple actuation modes for sophisticated movements. Examples across literature illustrate the development of soft actuators as free-moving, entirely soft-bodied robots with multiple locomotion gaits via careful manipulation of external stimuli. The review further highlights how the application of soft functional materials into robots with rigid components further enhances their locomotive abilities. Finally, taking advantage of the shape-morphing properties of soft materials, reconfigurable soft robots have shown the capacity for adaptive gaits that enable transition across environments with different locomotive modes for optimal efficiency. Overall, soft materials enable varied multimodal motion in actuators and robots, positioning soft robotics to make real-world applications for intricate and challenging tasks.

Basal ganglia–spinal cord pathway that commands locomotor gait asymmetries in mice

The basal ganglia are essential for executing motor actions. How the basal ganglia engage spinal motor networks has remained elusive. Medullary Chx10 gigantocellular (Gi) neurons are required for turning gait programs, suggesting that turning gaits organized by the basal ganglia are executed via this descending pathway. Performing deep brainstem recordings of Chx10 Gi Ca2+ activity in adult mice, we show that striatal projection neurons initiate turning gaits via a dominant crossed pathway to Chx10 Gi neurons on the contralateral side. Using intersectional viral tracing and cell-type-specific modulation, we uncover the principal basal ganglia–spinal cord pathway for locomotor asymmetries in mice: basal ganglia → pontine reticular nucleus, oral part (PnO) → Chx10 Gi → spinal cord. Modulating the restricted PnO → Chx10 Gi pathway restores turning competence upon striatal damage, suggesting that dysfunction of this pathway may contribute to debilitating turning deficits observed in Parkinson’s disease. Our results reveal the stratified circuit architecture underlying a critical motor program.

Bioelectric control of locomotor gaits in the walking ciliate Euplotes

Diverse animal species exhibit highly stereotyped behavioral actions and locomotor sequences as they explore their natural environments. In many such cases, the neural basis of behavior is well established, where dedicated neural circuitry contributes to the initiation and regulation of certain response sequences. At the microscopic scale, single-celled eukaryotes (protists) also exhibit remarkably complex behaviors and yet are completely devoid of nervous systems. Here, to address the question of how single cells control behavior, we study locomotor patterning in the exemplary hypotrich ciliate Euplotes, a highly polarized cell, which actuates a large number of leg-like appendages called cirri (each a bundle of ∼25-50 cilia) to swim in fluids or walk on surfaces. As it navigates its surroundings, a walking Euplotes cell is routinely observed to perform side-stepping reactions, one of the most sophisticated maneuvers ever observed in a single-celled organism. These are spontaneous and stereotyped reorientation events involving a transient and fast backward motion followed by a turn. Combining high-speed imaging with simultaneous time-resolved electrophysiological recordings, we show that this complex coordinated motion sequence is tightly regulated by rapid membrane depolarization events, which orchestrate the activity of different cirri on the cell. Using machine learning and computer vision methods, we map detailed measurements of cirri dynamics to the cell's membrane bioelectrical activity, revealing a differential response in the front and back cirri. We integrate these measurements with a minimal model to understand how Euplotes-a unicellular organism-manipulates its membrane potential to achieve real-time control over its motor apparatus.

Golexanolone reduces glial activation in the striatum and improves non-motor and some motor alterations in a rat model of Parkinson's disease.

Parkinson's disease (PD) affects more than 6 million people worldwide. Along with motor impairments, patients and animal models exhibiting PD symptoms also experience cognitive impairment, fatigue, anxiety, and depression. Currently, there are no drugs available for PD that alter the progression of the disease. A body of evidence suggests that increased GABA levels contribute to the reduced expression of tyrosine hydroxylase (TH) and accompanying behavioral deficits. TH expression may be restored by blocking GABAA receptors. We hypothesized that golexanolone (GR3027), a well-tolerated GABAA receptor-modulating steroid antagonist (GAMSA), may improve Parkinson's symptoms in a rat model of PD. The aims of this study were to assess whether golexanolone can ameliorate motor and non-motor symptoms in a rat model of PD and to identify some underlying mechanisms. We used the unilateral 6-OHDA rat model of PD. The golexanolone treatment started 4 weeks after surgery. Motor symptoms were assessed using Motorater and CatWalk tests. We also analyzed fatigue (using a treadmill test), anhedonia (via the sucrose preference test), anxiety (with an open field test), and short-term memory (using a Y maze). Glial activation and key proteins involved in PD pathogenesis were analyzed using immunohistochemistry and Western blot. Rats with PD showed motor incoordination and impaired locomotor gait, increased fatigue, anxiety, depression, and impaired short-term memory. Golexanolone treatment led to improvements in motor incoordination, certain aspects of locomotor gait, fatigue, anxiety, depression, and short-term memory. Notably, golexanolone reduced the activation of microglia and astrocytes, mitigated TH loss at 5 weeks after surgery, and prevented the increase of α-synuclein levels at 10 weeks. Golexanolone may be useful in improving both motor and non-motor symptoms that adversely affect the quality of life in PD patients, such as anxiety, depression, fatigue, motor coordination, locomotor gait, and certain cognitive alterations.

Golexanolone improves fatigue, motor incoordination and gait and memory in rats with bile duct ligation.

Many patients with the chronic cholestatic liver disease primary biliary cholangitis (PBC) show fatigue and cognitive impairment that reduces their quality of life. Likewise, rats with bile duct ligation (BDL) are a model of cholestatic liver disease. Current PBC treatments do not improve symptomatic alterations such as fatigue or cognitive impairment and new, more effective treatments are therefore required. Golexanolone reduces the potentiation of GABAA receptors activation by neurosteroids. Golexanolone reduces peripheral inflammation and neuroinflammation and improves cognitive and motor function in rats with chronic hyperammonemia. The aims of the present study were to assess if golexanolone treatment improves fatigue and cognitive and motor function in cholestatic BDL rats and if this is associated with improvement of peripheral inflammation, neuroinflammation, and GABAergic neurotransmission in the cerebellum. Rats were subjected to bile duct ligation. One week after surgery, oral golexanolone was administered daily to BDL and sham-operated controls. Fatigue was analysed in the treadmill, motor coordination in the motorater, locomotor gait in the Catwalk, and short-term memory in the Y-maze. We also analysed peripheral inflammation, neuroinflammation, and GABAergic neurotransmission markers by immunohistochemistry and Western blot. BDL induces fatigue, impairs memory and motor coordination, and alters locomotor gait in cholestatic rats. Golexanolone improves these alterations, and this was associated with improvement of peripheral inflammation, neuroinflammation, and GABAergic neurotransmission in the cerebellum. Golexanolone may have beneficial effects to treat fatigue, and motor and cognitive impairment in patients with the chronic cholestatic liver disease PBC.

Adaptive walking control for quadruped robot by using oscillation patterns.

To improve the adaptability of quadruped robot in multiple scenarios, an adaptive locomotive system based on the double-layered central pattern generator (CPG) is proposed. The novel CPG network consists of double master units and subsets of slave units based on gyroscope signals including yaw and pitch angle. The response of master units provides the ability to control the 1st joins of quadruped robot, while slave units can generate the symmetry signals to control the 2nd and 3rd joints. The CPG network enables the seamless switching of locomotion gaits to stops and starts by using an ultrasonic sensor. Through adjusting the mutually dependent parameters, joints can generate the joint angles to achieve steering behavior. For adaptive movement on an irregular surface, stable ranges of the robot body yaw and pitch angles are proposed by using gyroscope signals. The experimental results verify that the quadruped robot with the proposed double-layered CPG network can perform stable trot pattern in a complex environment.

Adaptive micro-locomotion in a dynamically changing environment via context detection

Substantial efforts have exploited reinforcement learning (RL) in the development of micro-robotic locomotion. These RL-powered micro-robots are capable of learning a locomotory policy based on their experience interacting with the surroundings, without requiring prior knowledge on the physics of locomotion in that environment. However, in their applications, micro-robots often encounter changes in the environment and need to adapt their locomotory gaits like living organisms in order to achieve robust locomotion performance. In standard RL methods, such a non-stationary environment can cause the micro-robots to continuously relearn the policy from scratch, degrading their locomotion performance. In this work, we explore a first use of a recently developed context detection method combined with deep RL to facilitate micro-robotic locomotion in a dynamically changing environment. As a proof-of-principle, we consider a simple micro-robot immersed in non-stationary environments switching between a viscous fluid environment and a dry frictional environment. We show that the RL with context detection approach enables the micro-robot to effectively detect changes in the environment and deploy specialized locomotory gaits for different environments accordingly to achieve significantly improved locomotion. Our results suggest the integration of deep RL with context detection as a potential tool for robust micro-robotic locomotion across different environments.

Effects of high-intensity gait training with and without soft robotic exosuits in people post-stroke: a development-of-concept pilot crossover trial

IntroductionHigh-intensity gait training is widely recognized as an effective rehabilitation approach after stroke. Soft robotic exosuits that enhance post-stroke gait mechanics have the potential to improve the rehabilitative outcomes achieved by high-intensity gait training. The objective of this development-of-concept pilot crossover study was to evaluate the outcomes achieved by high-intensity gait training with versus without soft robotic exosuits.MethodsIn this 2-arm pilot crossover study, four individuals post-stroke completed twelve visits of speed-based, high-intensity gait training: six consecutive visits of Robotic Exosuit Augmented Locomotion (REAL) gait training and six consecutive visits without the exosuit (CONTROL). The intervention arms were counterbalanced across study participants and separated by 6 + weeks of washout. Walking function was evaluated before and after each intervention using 6-minute walk test (6MWT) distance and 10-m walk test (10mWT) speed. Moreover, 10mWT speeds were evaluated before each training visit, with the time-course of change in walking speed computed for each intervention arm. For each participant, changes in each outcome were compared to minimal clinically-important difference (MCID) thresholds. Secondary analyses focused on changes in propulsion mechanics and associated biomechanical metrics.ResultsLarge between-group effects were observed for 6MWT distance (d = 1.41) and 10mWT speed (d = 1.14). REAL gait training resulted in an average pre-post change of 68 ± 27 m (p = 0.015) in 6MWT distance, compared to a pre-post change of 30 ± 16 m (p = 0.035) after CONTROL gait training. Similarly, REAL training resulted in a pre-post change of 0.08 ± 0.03 m/s (p = 0.012) in 10mWT speed, compared to a pre-post change of 0.01 ± 06 m/s (p = 0.76) after CONTROL. For both outcomes, 3 of 4 (75%) study participants surpassed MCIDs after REAL training, whereas 1 of 4 (25%) surpassed MCIDs after CONTROL training. Across the training visits, REAL training resulted in a 1.67 faster rate of improvement in walking speed. Similar patterns of improvement were observed for the secondary gait biomechanical outcomes, with REAL training resulting in significantly improved paretic propulsion for 3 of 4 study participants (p < 0.05) compared to 1 of 4 after CONTROL.ConclusionSoft robotic exosuits have the potential to enhance the rehabilitative outcomes produced by high-intensity gait training after stroke. Findings of this development-of-concept pilot crossover trial motivate continued development and study of the REAL gait training program.

Elegant Nematodes Improve Our Understanding of Human Neuronal Diseases, the Role of Pollutants and Strategies of Resilience.

The prevalence of neurodegenerative disorders such as Alzheimer's and Parkinson's disease are rising globally. The role of environmental pollution in neurodegeneration is largely unknown. Thus, this perspective advocates exposome research in C. elegans models of human diseases. The models express amyloid proteins such as Aβ, recapitulate the degeneration of specifically vulnerable neurons and allow for correlated neurobehavioral phenotyping throughout the entire life span of the nematode. Neurobehavioral traits like locomotion gaits, rigidity, or cognitive decline are quantifiable and carefully mimic key aspects of the human diseases. Underlying molecular pathways of neurodegeneration are elucidated in pollutant-exposed C. elegans Alzheimer's or Parkinson's models by transcriptomics (RNA-seq), mass spectrometry-based proteomics and omics addressing other biochemical traits. Validation of the identified disease pathways can be achieved by genome-wide association studies in matching human cohorts. A consistent One Health approach includes isolation of nematodes from contaminated sites and their comparative investigation by imaging, neurobehavioral profiling and single worm proteomics. C. elegans models of neurodegenerative diseases are likewise well-suited for high throughput methods that provide a promising strategy to identify resilience pathways of neurosafety and keep up with the number of pollutants, nonchemical exposome factors, and their interactions.